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nips2019_paper_name.txt
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nips2019_paper_name.txt
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Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation OOO
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks OOO OOO
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers OOO
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video OOO OOO
Zero-shot Learning via Simultaneous Generating and Learning OOO OOO
Ask not what AI can do for you, but what AI should do: Towards a framework of task delegability
Stand-Alone Self-Attention in Vision Models OOO
High Fidelity Video Prediction with Large Neural Nets OOO OOO
Unsupervised learning of object structure and dynamics from videos OOO OOO
TensorPipe: Easy Scaling with Micro-Batch Pipeline Parallelism
Meta-Learning with Implicit Gradients OOO
Adversarial Examples Are Not Bugs, They Are Features OOO
Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks OOO OOO OOO OOO
FreeAnchor: Learning to Match Anchors for Visual Object Detection OOO
Differentially Private Hypothesis Selection
New Differentially Private Algorithms for Learning Mixtures of Well-Separated Gaussians
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
Multi-Resolution Weak Supervision for Sequential Data OOO
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision OOO
The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice Detection OOO OOO
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle OOO
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance OOO
Generalized Sliced Wasserstein Distances
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
Blind Super-Resolution Kernel Estimation using an Internal-GAN OOO OOO
Noise-tolerant fair classification OOO
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection OOO OOO OOO
Joint-task Self-supervised Learning for Temporal Correspondence
Provable Gradient Variance Guarantees for Black-Box Variational Inference
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation OOO
Experience Replay for Continual Learning
Deep ReLU Networks Have Surprisingly Few Activation Patterns OOO
Chasing Ghosts: Instruction Following as Bayesian State Tracking OOO OOO
Block Coordinate Regularization by Denoising OOO
Reducing Noise in GAN Training with Variance Reduced Extragradient OOO
Learning Erdos-Renyi Random Graphs via Edge Detecting Queries OOO OOO
A Primal-Dual link between GANs and Autoencoders OOO
muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking OOO OOO
Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation OOO OOO
Invert to Learn to Invert
Equitable Stable Matchings in Quadratic Time
Zero-Shot Semantic Segmentation OOO OOO
Metric Learning for Adversarial Robustness OOO OOO
DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction OOO OOO
Batched Multi-armed Bandits Problem
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning OOO OOO OOO OOO
Differentially Private Bayesian Linear Regression OOO
Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos OOO
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling
CPM-Nets: Cross Partial Multi-View Networks OOO
Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis
Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling OOO
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
Importance Weighted Hierarchical Variational Inference
RSN: Randomized Subspace Newton
Trust Region-Guided Proximal Policy Optimization OOO
Adversarial Self-Defense for Cycle-Consistent GANs OOO OOO
Towards closing the gap between the theory and practice of SVRG
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control OOO
ETNet: Error Transition Network for Arbitrary Style Transfer OOO
No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
Deep Equilibrium Models
Saccader: Accurate, Interpretable Image Classification with Hard Attention OOO OOO OOO
Multiway clustering via tensor block models OOO
Regret Minimization for Reinforcement Learning on Multi-Objective Online Markov Decision Processes OOO OOO
NAT: Neural Architecture Transformer for Accurate and Compact Architectures OOO
Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor Regression OOO
Network Pruning via Transformable Architecture Search OOO OOO OOO
Differentiable Cloth Simulation for Inverse Problems
Poisson-randomized Gamma Dynamical Systems
Volumetric Correspondence Networks for Optical Flow OOO OOO
Learning Conditional Deformable Templates with Convolutional Networks OOO
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data OOO
Efficient Symmetric Norm Regression via Linear Sketching OOO
RUBi: Reducing Unimodal Biases in Visual Question Answering
Reducing Scene Bias of Convolutional Neural Networks for Human Action Understanding OOO
NeurVPS: Neural Vanishing Point Scanning via Conic Convolution
DATA: Differentiable ArchiTecture Approximation OOO
Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge OOO OOO
Memory-oriented Decoder for Light Field Salient Object Detection OOO
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition OOO OOO
Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels
Powerset Convolutional Neural Networks OOO
Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
Efficient 3D Deep Learning via Point-Based Representation and Voxel-Based Convolution OOO OOO
Deep Learning without Weight Transport
Combinatorial Bandits with Relative Feedback
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme
Joint Optimizing of Cycle-Consistent Networks OOO
Explicit Disentanglement of Appearance and Perspective in Generative Models OOO
Polynomial Cost of Adaptation for X-Armed Bandits
Learning to Propagate for Graph Meta-Learning OOO OOO
Secretary Ranking with Minimal Inversions
Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes OOO
Learning Perceptual Inference by Contrasting
Selecting the independent coordinates of manifolds with large aspect ratios
Region-specific Diffeomorphic Metric Mapping
Subset Selection via Supervised Facility Location
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations OOO OOO OOO
Reconciling λ-Returns with Experience Replay
Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs
A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation OOO
Combinatorial Inference against Label Noise
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning OOO OOO
Convolution with even-sized kernels and symmetric padding
On The Classification-Distortion-Perception Tradeoff OOO
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up OOO
Online sampling from log-concave distributions OOO
Envy-Free Classification OOO
Finding Friend and Foe in Multi-Agent Games
Computer Vision with a Single (Robust) Classifier
Gated CRF Loss for Weakly Supervised Semantic Image Segmentation OOO
Model Compression with Adversarial Robustness: A Unified Optimization Framework OOO OOO OOO
Neuron Communication Networks OOO
CondConv: Conditionally Parameterized Convolutions for Efficient Inference
Regression Planning Networks OOO OOO
Twin Auxilary Classifiers GAN OOO
Conditional Structure Generation through Graph Variational Generative Adversarial Nets OOO OOO OOO OOO
Distributional Policy Optimization: An Alternative Approach for Continuous Control OOO
Sampling Sketches for Concave Sublinear Functions of Frequencies
Deliberative Explanations: visualizing network insecurities OOO OOO
Computing Full Conformal Prediction Set with Approximate Homotopy
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift OOO
Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards OOO
Multi-View Reinforcement Learning OOO
Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution OOO
Neural Diffusion Distance for Image Segmentation OOO
Fine-grained Optimization of Deep Neural Networks OOO OOO
Extending Stein’s Unbiased Risk Estimator To Train Deep Denoisers with Correlated Pairs of Noisy Images OOO
Wibergian Learning of Continuous Energy Functions
Hyperspherical Prototype Networks OOO
Expressive power of tensor-network factorizations for probabilistic modelling OOO
HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs OOO OOO
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
Efficient Meta Learning via Minibatch Proximal Update
Unconstrained Monotonic Neural Networks OOO
Guided Similarity Separation for Image Retrieval
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss OOO
Strategizing against No-regret Learners
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs OOO OOO
Hierarchical Optimal Transport for Document Representation OOO
Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes OOO
Positional Normalization
A New Defense Against Adversarial Images: Turning a Weakness into a Strength OOO
Quadratic Video Interpolation OOO
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies OOO
Incremental Scene Synthesis
Self-Supervised Generalisation with Meta Auxiliary Learning
Variational Denoising Network: Toward Blind Noise Modeling and Removal OOO OOO
Fast Sparse Group Lasso
Learnable Tree Filter for Structure-preserving Feature Transform OOO
Data-Dependence of Plateau Phenomenon in Learning with Neural Network --- Statistical Mechanical Analysis OOO
Coordinated hippocampal-entorhinal replay as structural inference
Cascaded Dilated Dense Network with Two-step Data Consistency for MRI Reconstruction OOO OOO
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning OOO
On the Curved Geometry of Accelerated Optimization OOO
Multi-marginal Wasserstein GAN OOO
Better Exploration with Optimistic Actor Critic
Importance Resampling for Off-policy Prediction
The Label Complexity of Active Learning from Observational Data
Meta-Learning Representations for Continual Learning OOO OOO
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training OOO
Visualizing the PHATE of Neural Networks OOO
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers OOO
Nonconvex Low-Rank Tensor Completion from Noisy Data OOO
Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization OOO
Channel Gating Neural Networks OOO
Neural networks grown and self-organized by noise OOO OOO
Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning
Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting OOO
Variational Structured Semantic Inference for Diverse Image Captioning
Mapping State Space using Landmarks for Universal Goal Reaching
Transferable Normalization: Towards Improving Transferability of Deep Neural Networks OOO
Random deep neural networks are biased towards simple functions OOO
XNAS: Neural Architecture Search with Expert Advice OOO
CNN^{2}: Viewpoint Generalization via a Binocular Vision OOO
Generalized Off-Policy Actor-Critic
DAC: The Double Actor-Critic Architecture for Learning Options OOO
Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models OOO
Controlling Neural Level Sets
Blended Matching Pursuit
An Improved Analysis of Training Over-parameterized Deep Neural Networks OOO
Controllable Text to Image Generation OOO OOO
Improving Textual Network Learning with Variational Homophilic Embeddings OOO OOO OOO
Rethinking Generative Coverage: A Pointwise Guaranteed Approach OOO
The Randomized Midpoint Method for Log-Concave Sampling
Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update OOO
Fully Neural Network based Model for General Temporal Point Processes OOO
Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks OOO OOO
Discrimination in Online Markets: Effects of Social Bias on Learning from Reviews and Policy Design
Provably Powerful Graph Networks OOO OOO
Order Optimal One-Shot Distributed Learning OOO
Information Competing Process for Learning Diversified Representations OOO
GENO -- GENeric Optimization for Classical Machine Learning OOO
Conditional Independence Testing using Generative Adversarial Networks OOO OOO OOO
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function
Partitioning Structure Learning for Segmented Linear Regression Trees OOO
A Tensorized Transformer for Language Modeling OOO
Kernel Stein Tests for Multiple Model Comparison
Disentangled behavioural representations OOO
More Is Less: Learning Efficient Video Representations by Temporal Aggregation Module OOO OOO
Rethinking the CSC Model for Natural Images
Integrating Generative and Discriminative Sparse Kernel Machines for Multi-class Active Learning OOO
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity
Perceiving the arrow of time in autoregressive motion
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections OOO
Hyper-Graph-Network Decoders for Block Codes OOO OOO
Large Scale Markov Decision Processes with Changing Rewards OOO
Multiview Aggregation for Learning Category-Specific Shape Reconstruction OOO
Semi-Parametric Dynamic Contextual Pricing OOO
Nearly Linear-Time, Deterministic Algorithm for Maximizing (Non-Monotone) Submodular Functions Under Cardinality Constraint
Initialization of ReLUs for Dynamical Isometry
Gradient Information for Representation and Modeling OOO
SpiderBoost and Momentum: Faster Variance Reduction Algorithms
Minimax rates of estimating approximate differential privacy
Backprop with Approximate Activations for Memory-efficient Network Training OOO
Training Image Estimators without Image Ground Truth
Deep Structured Prediction for Facial Landmark Detection OOO
Information-Theoretic Confidence Bounds for Reinforcement Learning OOO
Transfer Anomaly Detection by Inferring Latent Domain Representations OOO OOO
Total Least Squares Regression in Input Sparsity Time OOO
Park: An Open Platform for Learning-Augmented Computer Systems
Adapting Neural Networks for the Estimation of Treatment Effects OOO
Learning Transferable Graph Exploration OOO
Conformal Prediction Under Covariate Shift
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation OOO
Asymmetric Valleys: Beyond Sharp and Flat Local Minima
Positive-Unlabeled Compression on the Cloud OOO
Direct Estimation of Differential Functional Graphical Model OOO
On the Calibration of Multiclass Classification with Rejection OOO
Third-Person Visual Imitation Learning via Decoupled Hierarchical Control
Stagewise Training Accelerates Convergence of Testing Error Over SGD
Learning Robust Options by Conditional Value at Risk Optimization OOO
Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems
On Learning Over-parameterized Neural Networks: A Functional Approximation Prospective OOO
Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries OOO
Visual Sequence Learning in Hierarchical Prediction Networks and Primate Visual Cortex OOO
Dual Variational Generation for Low Shot Heterogeneous Face Recognition OOO OOO
Discovering Neural Wirings
On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems OOO
Knowledge Extraction with No Observable Data
PAC-Bayes under potentially heavy tails OOO
One-Shot Object Detection with Co-Attention and Co-Excitation OOO OOO OOO
Quaternion Knowledge Graph Embeddings OOO OOO
Glyce: Glyph-vectors for Chinese Character Representations OOO
Turbo Autoencoder: Deep learning based channel code for point-to-point communication channels
Heterogeneous Graph Learning for Visual Commonsense Reasoning OOO
Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning OOO OOO
Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components OOO
Identifying Causal Effects via Context-specific Independence Relations OOO
Bridging Machine Learning and Logical Reasoning by Abductive Learning OOO
Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function OOO
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization OOO
Regularizing Trajectory Optimization with Denoising Autoencoders OOO OOO OOO
Learning Hierarchical Priors in VAEs OOO
Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits
Safe Exploration for Interactive Machine Learning OOO
Addressing Failure Detection by Learning Model Confidence OOO
Combinatorial Bayesian Optimization using the Graph Cartesian Product OOO OOO
Fooling Neural Network Interpretations via Adversarial Model Manipulation OOO OOO OOO
On Lazy Training in Differentiable Programming
Quality Aware Generative Adversarial Networks OOO OOO OOO
Copula-like Variational Inference
Implicit Regularization for Optimal Sparse Recovery
Locally Private Gaussian Estimation
Multi-mapping Image-to-Image Translation via Learning Disentanglement
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs OOO
Structured Decoding for Non-Autoregressive Machine Translation
Learning Temporal Pose Estimation from Sparsely-Labeled Videos OOO OOO
Greedy InfoMax for Biologically Plausible Self-Supervised Representation Learning OOO
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching OOO
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition OOO OOO OOO
Real-Time Reinforcement Learning OOO
Robust Multi-agent Counterfactual Prediction
Approximate Inference Turns Deep Networks into Gaussian Processes OOO OOO
Deep Signatures
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
Convergent Policy Optimization for Safe Reinforcement Learning OOO OOO
Augmented Neural ODEs
Thompson Sampling for Multinomial Logit Contextual Bandits OOO
Backpropagation-Friendly Eigendecomposition
FastSpeech: Fast, Robust and Controllable Text to Speech OOO
Ultrametric Fitting by Gradient Descent
Distinguishing Distributions When Samples Are Strategically Transformed OOO
Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks OOO
Deep Set Prediction Networks OOO
DppNet: Approximating Determinantal Point Processes with Deep Networks OOO
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control OOO
Neural Lyapunov Control
Fully Dynamic Consistent Facility Location
A Stickier Benchmark for General-Purpose Language Understanding Systems OOO OOO OOO
A Flexible Generative Framework for Graph-based Semi-supervised Learning OOO OOO OOO
Self-normalization in Stochastic Neural Networks OOO
Optimal Decision Tree with Noisy Outcomes OOO
Meta-Curvature
Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning OOO
KerGM: Kernelized Graph Matching OOO
Transfusion: Understanding Transfer Learning for Medical Imaging
Adversarial training for free! OOO
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
Implicitly learning to reason in first-order logic
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
Arbicon-Net: Arbitrary Continuous Geometric Transformation Networks for Image Registration OOO
Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric OOO
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models OOO OOO
First order expansion of convex regularized estimators
Capacity Bounded Differential Privacy
Universal Boosting Variational Inference OOO
SGD on Neural Networks Learns Functions of Increasing Complexity OOO
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk
Making AI Forget You: Data Deletion in Machine Learning OOO
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition
Conformalized Quantile Regression OOO
Thompson Sampling with Information Relaxation Penalties
Deep Generalized Method of Moments for Instrumental Variable Analysis
Learning Sample-Specific Models with Low-Rank Personalized Regression OOO
Dance to Music
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
Implicit Generation and Modeling with Energy Based Models OOO
Who Learns? Decomposing Learning into Per-Parameter Loss Contribution
Predicting the Politics of an Image Using Webly Supervised Data
Adaptive GNN for Image Analysis and Editing OOO
Ultra Fast Medoid Identification via Correlated Sequential Halving
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD
Asymptotics for Sketching in Least Squares Regression OOO
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Exact inference in structured prediction
Coda: An End-to-End Neural Program Decompiler
Bat-G net: Bat-inspired High-Resolution 3D Image Reconstruction using Ultrasonic Echoes OOO OOO OOO
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data OOO OOO
Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation OOO OOO
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy OOO
Learning Representations for Time Series Clustering OOO OOO
Variance Reduced Uncertainty Calibration
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits OOO
Unsupervised Keypoint Learning for Guiding Class-conditional Video Prediction OOO OOO
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks OOO
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction OOO
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling
Cross-sectional Learning of Extremal Dependence among Financial Assets
Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG OOO
Compression with Flows via Local Bits-Back Coding OOO OOO
Exact Rate-Distortion in Autoencoders via Echo Noise OOO
iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
Self-Supervised Active Triangulation for 3D Human Pose Reconstruction OOO OOO
MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization OOO
Improved Precision and Recall Metric for Assessing Generative Models OOO
A First-order Algorithmic Framework for Distributionally Robust Logistic Regression OOO
PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph OOO OOO
Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems OOO
Learning Generalizable Device Placement Algorithms for Distributed Machine Learning OOO
Uncoupled Regression from Pairwise Comparison Data OOO
Cross Attention Network for Few-shot Classification OOO OOO OOO OOO
A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models OOO
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs OOO OOO
Teaching Multiple Concepts to a Forgetful Learner
Regularized Weighted Low Rank Approximation OOO
Practical and Consistent Estimation of f-Divergences
Approximation Ratios of Graph Neural Networks for Combinatorial Problems OOO OOO
Thinning for Accelerating the Learning of Point Processes
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models OOO
Differentially Private Markov Chain Monte Carlo OOO
Full-Gradient Representation for Neural Network Visualization OOO OOO
q-means: A quantum algorithm for unsupervised machine learning OOO OOO
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints OOO
Limitations of the empirical Fisher approximation
Flow-based Image-to-Image Translation with Feature Disentanglement OOO
Learning dynamic semi-algebraic proofs
Shape and Time Distorsion Loss for Training Deep Time Series Forecasting Models
Understanding attention in graph neural networks OOO OOO OOO
Data Cleansing for Models Trained with SGD
Curvilinear Distance Metric Learning OOO
Semantically-Regularized Logic Graph Embeddings OOO OOO
Modeling Uncertainty by Learning A Hierarchy of Deep Neural Connections
Efficient Graph Generation with Graph Recurrent Attention Networks OOO OOO OOO OOO
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms
Learning Deep Bilinear Transformation for Fine-grained Image Representation OOO
Practical Deep Learning with Bayesian Principles OOO
Training Language GANs from Scratch OOO OOO
Pseudo-Extended Markov chain Monte Carlo OOO
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate OOO
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters OOO
On Adversarial Mixup Resynthesis OOO
A Geometric Perspective on Optimal Representations for Reinforcement Learning OOO OOO
Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks OOO
Understanding and Improving Layer Normalization
Uncertainty-based Continual Learning with Adaptive Regularization
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning OOO
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging OOO OOO
Massively scalable Sinkhorn distances via the Nyström method
Double Quantization for Communication-Efficient Distributed Optimization OOO
Globally optimal score-based learning of directed acyclic graphs in high-dimensions OOO
Multi-relational Poincaré Graph Embeddings OOO OOO
No-Press Diplomacy: Modeling Multi-Agent Gameplay
State Aggregation Learning from Markov Transition Data OOO
Disentangling Influence: Using disentangled representations to audit model predictions OOO
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
Partially Encrypted Deep Learning using Functional Encryption
Decentralized Cooperative Stochastic Bandits
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem
Efficient Deep Approximation of GMMs
Learning low-dimensional state embeddings and metastable clusters from time series data OOO OOO
Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point Representations OOO OOO OOO OOO
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes OOO
Kernel Instrumental Variable Regression OOO
Symmetry-Based Disentangled Representation Learning requires Interaction with Environments OOO
Fast Efficient Hyperparameter Tuning for Policy Gradient Methods
Offline Contextual Bayesian Optimization OOO OOO
Making the Cut: A Bandit-based Approach to Tiered Interviewing
Unsupervised Scalable Representation Learning for Multivariate Time Series OOO OOO
A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI
End to end learning and optimization on graphs OOO OOO
Game Design for Eliciting Distinguishable Behavior
When does label smoothing help?
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning OOO
Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks OOO OOO OOO
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation OOO
Distribution-Independent PAC Learning of Halfspaces with Massart Noise OOO
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies OOO
Online Learning for Auxiliary Task Weighting for Reinforcement Learning OOO
Blocking Bandits
Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
Prior-Free Dynamic Auctions with Low Regret Buyers
On Single Source Robustness in Deep Fusion Models
Policy Evaluation with Latent Confounders via Optimal Balance
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting OOO
Adaptive Cross-Modal Few-shot Learning OOO
Spectral Modification of Graphs for Improved Spectral Clustering OOO OOO
Hyperbolic Graph Convolutional Neural Networks OOO OOO
Cost Effective Active Search
Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks OOO
A Stratified Approach to Robustness for Randomly Smoothed Classifiers
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces OOO
Fair Algorithms for Clustering OOO
Learning Mean-Field Games
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers OOO OOO
Deep imitation learning for molecular inverse problems
Visual Concept-Metaconcept Learning
Adaptive Video-to-Video Synthesis via Network Weight Generation OOO OOO OOO
Neural Similarity Learning
Ordered Memory
MixMatch: A Holistic Approach to Semi-Supervised Learning OOO
Deep Multivariate Quantiles for Novelty Detection OOO
Fast Parallel Algorithms for Statistical Subset Selection Problems
PHYRE: A New Benchmark for Physical Reasoning OOO
How many variables should be entered in a principal component regression equation? OOO
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery OOO
Mutually Regressive Point Processes
Data-driven Estimation of Sinusoid Frequencies
E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving OOO
ANODEV2: A Coupled Neural ODE Framework
Estimating Entropy of Distributions in Constant Space OOO
On the Utility of Learning about Humans for Human-AI Coordination
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium
Learning in Generalized Linear Contextual Bandits with Stochastic Delays OOO
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions OOO
On Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
On the Accuracy of Influence Functions for Measuring Group Effects
Face Reconstruction from Voice using Generative Adversarial Networks OOO OOO OOO OOO
Incremental Few-Shot Learning with Attention Attractor Networks OOO OOO OOO
On Testing for Biases in Peer Review
Learning Disentangled Representation for Robust Person Re-identification OOO
Balancing Efficiency and Fairness in On-Demand Ridesourcing
Latent Ordinary Differential Equations for Irregularly-Sampled Time Series
Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
Input Similarity from the Neural Network Perspective OOO
Adaptive Sequence Submodularity
Weight Agnostic Neural Networks OOO
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
Reducing the variance in online optimization by transporting past gradients OOO
Characterizing Bias in Classifiers using Generative Models OOO
Optimal Stochastic and Online Learning with Individual Iterates
Policy Learning for Fairness in Ranking
Off-Policy Evaluation of Generalization for Deep Q-Learning in Binary Reward Tasks
Regularized Gradient Boosting OOO
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Markov Random Fields for Collaborative Filtering OOO
A Step Toward Quantifying Independently Reproducible Machine Learning Research OOO
Scalable Global Optimization via Local Bayesian Optimization OOO
Time-series Generative Adversarial Networks OOO OOO OOO
On Accelerating Training of Transformer-Based Language Models OOO
A Refined Margin Distribution Analysis for Forest Representation Learning OOO OOO
Robustness to Adversarial Perturbations in Learning from Incomplete Data OOO
Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks OOO
An Adaptive Empirical Bayesian Method for Sparse Deep Learning OOO
Adaptive Influence Maximization with Myopic Feedback
Focused Quantization for Sparse CNNs OOO
Quantum Embedding of Knowledge for Reasoning OOO
Optimal Best Markovian Arm Identification with Fixed Confidence OOO
Limiting Extrapolation in Linear Approximate Value Iteration
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model OOO
Invertible Convolutional Flow OOO
A Latent Variational Framework for Stochastic Optimization OOO
Topology-Preserving Deep Image Segmentation OOO
Connective Cognition Network for Directional Visual Commonsense Reasoning OOO
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms OOO
A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning OOO
Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently
Learning Disentangled Representations for Recommendation OOO
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels OOO OOO
In-Place Near Zero-Cost Memory Protection for DNN
Acceleration via Symplectic Discretization of High-Resolution Differential Equations OOO
XLNet: Generalized Autoregressive Pretraining for Language Understanding OOO OOO
Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex OOO
Mixtape: Breaking the Softmax Bottleneck Efficiently
Variance Reduced Policy Evaluation with Smooth Function Approximation
Learning GANs and Ensembles Using Discrepancy OOO
Co-Generation with GANs using AIS based HMC OOO
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification OOO OOO OOO OOO
Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs OOO
Abstract Reasoning with Distracting Features
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer
Adversarial Training and Robustness for Multiple Perturbations OOO
Doubly-Robust Lasso Bandit
DM2C: Deep Mixed-Modal Clustering OOO
MaCow: Masked Convolutional Generative Flow OOO OOO
Learning by Abstraction: The Neural State Machine for Visual Reasoning
Adaptive Gradient-Based Meta-Learning Methods OOO
Equipping Experts/Bandits with Long-term Memory
A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning OOO
Scalable inference of topic evolution via models for latent geometric structures
Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network OOO OOO OOO
Deep Active Learning with a Neural Architecture Search OOO
Efficiently escaping saddle points on manifolds
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks OOO
DFNets: Spectral CNNs for Graphs with Feedback-looped Filters OOO OOO
Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning OOO OOO
Comparing Unsupervised Word Translation Methods Step by Step OOO
Learning from Crap Data via Generation OOO
Constrained deep neural network architecture search for IoT devices accounting hardware calibration OOO OOO
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection OOO
Iterative Least Trimmed Squares for Mixed Linear Regression OOO
Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces
Divergence-Augmented Policy Optimization OOO
Intrinsic dimension of data representations in deep neural networks OOO OOO
Towards a Zero-One Law for Column Subset Selection
Compositional De-Attention Networks OOO OOO
Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning OOO OOO OOO
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers OOO
Mining GOLD Samples for Conditional GANs OOO
Deep Model Transferability from Attribution Maps
Fully Parameterized Quantile Function for Distributional Reinforcement Learning OOO OOO
Direct Optimization through $\arg \max$ for Discrete Variational Auto-Encoder OOO OOO
Distributional Reward Decomposition for Reinforcement Learning OOO OOO
L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise OOO
Convergence Guarantees for Adaptive Bayesian Quadrature Methods OOO
Progressive Augmentation of GANs OOO
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization OOO
Meta-Surrogate Benchmarking for Hyperparameter Optimization OOO OOO
Learning to Perform Local Rewriting for Combinatorial Optimization OOO
Anti-efficient encoding in emergent communication
Singleshot : a scalable Tucker tensor decomposition
Neural Machine Translation with Soft Prototype
Reliable training and estimation of variance networks OOO
On the Statistical Properties of Multilabel Learning
Bayesian Learning of Sum-Product Networks OOO OOO
Bayesian Batch Active Learning as Sparse Subset Approximation OOO
Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks OOO OOO
Variational Bayesian Decision-making for Continuous Utilities OOO
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks OOO
Single-Model Uncertainties for Deep Learning
Is Deeper Better only when Shallow is Good?
Wasserstein Weisfeiler-Lehman Graph Kernels OOO
Domain Generalization via Model-Agnostic Learning of Semantic Features
Grid Saliency for Context Explanations of Semantic Segmentation OOO OOO OOO
First-order methods almost always avoid saddle points: The case of Vanishing step-sizes
Maximum Mean Discrepancy Gradient Flow OOO
Oblivious Sampling Algorithms for Private Data Analysis
Semi-supervisedly Co-embedding Attributed Networks OOO OOO OOO
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI OOO
Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders OOO
Nonstochastic Multiarmed Bandits with Unrestricted Delays
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling OOO
Code Generation as Dual Task of Code Summarization OOO
Diffeomorphic Temporal Alignment Networks OOO
Weakly Supervised Instance Segmentation using the Bounding Box Tightness Prior OOO
On the Power and Limitations of Random Features for Understanding Neural Networks OOO
Efficient Pure Exploration in Adaptive Round model
Multi-objects Generation with Amortized Structural Regularization OOO
Neural Shuffle-Exchange Networks - Sequence Processing in O(n log n) Time OOO
DetNAS: Backbone Search for Object Detection OOO OOO
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates OOO
Fast AutoAugment
On the Convergence Rate of Training Recurrent Neural Networks in the Overparameterized Regime OOO
Interval timing in deep reinforcement learning agents OOO
Graph-based Discriminators: Sample Complexity and Expressiveness OOO
Large Scale Structure of Neural Network Loss Landscapes OOO
Learning Nonsymmetric Determinantal Point Processes
Hypothesis Set Stability and Generalization
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds OOO OOO
Precision-Recall Balanced Topic Modelling
Learning Sparse Distributions using Iterative Hard Thresholding OOO
Discriminative Topic Modeling with Logistic LDA
Quantum Wasserstein Generative Adversarial Networks OOO OOO OOO
Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion OOO
Hyperparameter Learning via Distributional Transfer OOO
Discriminator optimal transport
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes OOO
Are Anchor Points Really Indispensable in Label-Noise Learning?
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations OOO OOO
Differentiable Sorting using Optimal Transport: The Sinkhorn CDF and Quantile Operator
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks OOO OOO
Likelihood-Free Overcomplete ICA and ApplicationsIn Causal Discovery
Interior-point Methods Strike Back: Solving the Wasserstein Barycenter Problem
Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs OOO OOO
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections
Efficient Non-Convex Stochastic Compositional Optimization Algorithm via Stochastic Recursive Gradient Descent OOO
On the convergence of single-call stochastic extra-gradient methods
Infra-slow brain dynamics as a marker for cognitive function and decline
Robust Principle Component Analysis with Adaptive Neighbors
High-Quality Self-Supervised Deep Image Denoising OOO
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup OOO
GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs OOO
Online Prediction of Switching Graph Labelings with Cluster Specialists OOO OOO
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response OOO OOO
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning OOO
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off OOO
Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs OOO
Cross-lingual Language Model Pretraining OOO
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse OOO
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input OOO
Universal Invariant and Equivariant Graph Neural Networks OOO OOO
The bias of the sample mean in multi-armed bandits can be positive or negative
On the Correctness and Sample Complexity of Inverse Reinforcement Learning OOO
VIREL: A Variational Inference Framework for Reinforcement Learning OOO
First Order Motion Model for Image Animation
Tensor Monte Carlo: Particle Methods for the GPU era OOO
Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction OOO
Learning from Label Proportions with Generative Adversarial Networks OOO OOO OOO
Efficient and Thrifty Voting by Any Means Necessary
PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation OOO OOO OOO
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization OOO
Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning OOO OOO
Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning
Toward a Characterization of Loss Functions for Distribution Learning OOO
Coresets for Archetypal Analysis
Emergence of Object Segmentation in Perturbed Generative Models OOO OOO
Optimal Sparse Decision Trees OOO
Escaping from saddle points on Riemannian manifolds
Muti-source Domain Adaptation for Semantic Segmentation OOO
Localized Structured Prediction
Nonzero-sum Adversarial Hypothesis Testing Games OOO
Manifold-regression to predict from MEG/EEG brain signals without source modeling OOO
Modeling Tabular data using Conditional GAN OOO
Normalization Helps Training of Quantized LSTM
Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration
Deep Scale-spaces: Equivariance Over Scale
GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series OOO
Estimating Convergence of Markov chains with L-Lag Couplings OOO
Learning-Based Low-Rank Approximations OOO
Implicit Regularization in Deep Matrix Factorization
List-decodable Linear Regression OOO
Learning elementary structures for 3D shape generation and matching OOO OOO
On the Hardness of Robust Classification OOO
Foundations of Comparison-Based Hierarchical Clustering OOO
What the Vec? Towards Probabilistically Grounded Embeddings OOO
Minimizers of the Empirical Risk and Risk Monotonicity
Explicit Planning for Efficient Exploration in Reinforcement Learning OOO
Lower Bounds on Adversarial Robustness from Optimal Transport OOO
Neural Spline Flows OOO
Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization OOO OOO
Nonlinear scaling of resource allocation in sensory bottlenecks
Constrained Reinforcement Learning: A Dual Approach OOO
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules OOO OOO
An adaptive nearest neighbor rule for classification OOO
Coresets for Clustering with Fairness Constraints OOO
PerspectiveNet: A Scene-consistent Image Generator for New View Synthesis in Real Indoor Environments OOO
MAVEN: Multi-Agent Variational Exploration
Competitive Gradient Descent
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses
Continual Unsupervised Representation Learning OOO OOO
Self-Routing Capsule Networks OOO
The Parameterized Complexity of Cascading Portfolio Scheduling
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards OOO
Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes OOO
Sequence Modelling with Unconstrained Generation Order OOO
Probabilistic Logic Neural Networks for Reasoning OOO
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening OOO
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond OOO
The Implicit Bias of AdaGrad on Separable Data
On two ways to use determinantal point processes for Monte Carlo integration OOO
LiteEval: A Coarse-to-Fine Framework for Resource Efficient Video Recognition OOO OOO
How degenerate is the parametrization of neural networks with the ReLU activation function? OOO
Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks OOO
Re-examination of the Role of Latent Variables in Sequence Modeling
Max-value Entropy Search for Multi-Objective Bayesian Optimization OOO
Stein Variational Gradient Descent With Matrix-Valued Kernels
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms
Detecting Overfitting via Adversarial Examples OOO OOO
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies OOO OOO
Towards Understanding the Importance of Shortcut Connections in Residual Networks OOO
Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains
Solving Interpretable Kernel Dimensionality Reduction OOO
Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space OOO
A Model to Search for Synthesizable Molecules
Post training 4-bit quantization of convolutional networks for rapid-deployment OOO
Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes OOO
Differentially Private Anonymized Histograms
Dynamic Local Regret for Non-convex Online Forecasting
Learning Local Search Heuristics for Boolean Satisfiability
Provably Efficient Q-Learning with Low Switching Cost
Solving graph compression via optimal transport OOO OOO
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Stability of Graph Scattering Transforms OOO
A Debiased MDI Feature Importance Measure for Random Forests
Difference Maximization Q-learning: Provably Efficient Q-learning with Function Approximation
Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models OOO OOO
Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks OOO
Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices
Learning Distributions Generated by One-Layer ReLU Networks OOO OOO
Large-scale optimal transport map estimation using projection pursuit
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning OOO
On Exact Computation with an Infinitely Wide Neural Net OOO
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning OOO
Chirality Nets for Human Pose Regression OOO OOO OOO
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds OOO
Fast Decomposable Submodular Function Minimization using Constrained Total Variation
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
Spherical Text Embedding OOO OOO
Möbius Transformation for Fast Inner Product Search on Graph OOO
Hyperbolic Graph Neural Networks OOO OOO
Average Individual Fairness: Algorithms, Generalization and Experiments
Fixing the train-test resolution discrepancy OOO
Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes OOO
Manipulating a Learning Defender and Ways to Counteract
Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations OOO OOO
Learning to Infer Implicit Surfaces without 3D Supervision OOO
Fast and Accurate Least-Mean-Squares Solvers
Certifiable Robustness to Graph Perturbations OOO
Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay
Paradoxes in Fair Machine Learning OOO
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
The spiked matrix model with generative priors OOO
Gradient Dynamics of Shallow Low-Dimensional ReLU Networks OOO
Robust and Communication-Efficient Collaborative Learning
Multiclass Learning from Contradictions
Learning from Trajectories via Subgoal Discovery
Distributed Low-rank Matrix Factorization With Exact Consensus OOO
Online Normalization for Training Neural Networks OOO
The Synthesis of XNOR Recurrent Neural Networks with Stochastic Logic OOO
An adaptive Mirror-Prox method for variational inequalities with singular operators
N-Gram Graph: A Simple Unsupervised Representation for Molecules OOO OOO OOO
Characterizing the exact behaviors of temporal difference learning algorithms using Markov jump linear system theory OOO
Facility Location Problem in Differential Privacy Model Revisited
Revisiting Auxiliary Latent Variables in Generative Models OOO
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
A Universally Optimal Multistage Accelerated Stochastic Gradient Method
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Large Memory Layers with Product Keys
Learning Deterministic Weighted Automata with Queries and Counterexamples
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent OOO
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
Visualizing and Measuring the Geometry of BERT
Self-Critical Reasoning for Robust Visual Question Answering
Learning to Screen
A Communication Efficient Stochastic Multi-Block Alternating Direction Method of Multipliers
A Little Is Enough: Circumventing Defenses For Distributed Learning
Error Correcting Output Codes Improve Probability Estimation and Adversarial Robustness of Deep Neural Networks OOO OOO
A Robust Non-Clairvoyant Dynamic Mechanism for Contextual Auctions OOO
Finite-Sample Analysis for SARSA with Linear Function Approximation
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models OOO
Graph Structured Prediction Energy Networks OOO OOO
Private Learning Implies Online Learning: An Efficient Reduction
Graph Agreement Models for Semi-Supervised Learning OOO OOO
Latent distance estimation for random geometric graphs OOO
Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network OOO
The Functional Neural Process
Recurrent Registration Neural Networks for Deformable Image Registration OOO
Unsupervised State Representation Learning in Atari OOO OOO
Unlocking Fairness: a Trade-off Revisited
Fisher Efficient Inference of Intractable Models
Thompson Sampling and Approximate Inference
PRNet: Self-Supervised Learning for Partial-to-Partial Registration OOO
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making OOO
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians OOO
Learning Macroscopic Brain Connectomes via Group-Sparse Factorization
Approximating the Permanent by Sampling from Adaptive Partitions
Retrosynthesis Prediction with Conditional Graph Logic Network OOO OOO
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration
Online Learning via the Differential Privacy Lens
3D Object Detection from a Single RGB Image via Perspective Points OOO OOO
Parameter elimination in particle Gibbs sampling
This Looks Like That: Deep Learning for Interpretable Image Recognition OOO OOO
Adaptively Aligned Image Captioning via Adaptive Attention Time OOO
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning
Learning Bayesian Networks with Low Rank Conditional Probability Tables OOO OOO
Equal Opportunity in Online Classification with Partial Feedback OOO
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations OOO
Neural Multisensory Scene Inference
Regret Bounds for Thompson Sampling in Restless Bandit Problems
What Can ResNet Learn Efficiently, Going Beyond Kernels? OOO
Better Transfer Learning Through Inferred Successor Maps
Unsupervised Co-Learning on $G$-Manifolds Across Irreducible Representations OOO OOO
Defending Against Neural Fake News
Sample Adaptive MCMC
A Stochastic Composite Gradient Method with Incremental Variance Reduction
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses OOO
STAR-Caps: Capsule Networks with Straight-Through Attentive Routing OOO
Limitations of Lazy Training of Two-layers Neural Network OOO
Reconciling meta-learning and continual learning with online mixtures of tasks OOO
Distributionally Robust Optimization and Generalization in Kernel Methods OOO
A General Theory of Equivariant CNNs on Homogeneous Spaces OOO
Trivializations for Gradient-Based Optimization on Manifolds OOO
Write, Execute, Assess: Program Synthesis with a REPL
A Meta-Analysis of Overfitting in Machine Learning OOO
(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs OOO
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback
Sampling Networks and Aggregate Simulation for Online POMDP Planning OOO
Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks OOO
GNNExplainer: Generating Explanations for Graph Neural Networks OOO OOO OOO OOO
Linear Stochastic Bandits Under Safety Constraints
A coupled autoencoder approach for multi-modal analysis of cell types
Towards Automatic Concept-based Explanations OOO
A Deep Probabilistic Model for Compressing Low Resolution Videos OOO OOO OOO
Budgeted Reinforcement Learning in Continuous State Space OOO
The Discovery of Useful Questions as Auxiliary Tasks
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm
Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias
Correlation clustering with local objectives OOO
Multiclass Performance Metric Elicitation
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
Explicit Explore-Exploit Algorithms in Continuous State Spaces
ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
Understanding Posterior Collapse in Variational Autoencoders OOO
Language as an Abstraction for Hierarchical Deep Reinforcement Learning OOO OOO
Efficient online learning with kernels for adversarial large scale problems OOO
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning OOO
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models OOO OOO
Certified Adversarial Robustness with Addition Gaussian Noise OOO
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels
Non-Cooperative Inverse Reinforcement Learning OOO
DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization OOO
Sobolev Independence Criterion
Maximum Entropy Monte-Carlo Planning OOO
Learning from brains how to regularize machines
Using Statistics to Automate Stochastic Optimization OOO
Zero-shot Knowledge Transfer via Adversarial Belief Matching OOO OOO
Differentiable Convex Optimization Layers OOO
Random Tessellation Forests
Learning Nearest Neighbor Graphs from Noisy Distance Samples OOO
Lookahead Optimizer: k steps forward, 1 step back
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer OOO
Covariate-Powered Empirical Bayes Estimation OOO
Understanding the Role of Momentum in Stochastic Gradient Methods
A neurally plausible model for online recognition andpostdiction in a dynamical environment OOO
Guided Meta-Policy Search
Marginalized Off-Policy Evaluation for Reinforcement Learning OOO
Contextual Bandits with Cross-Learning OOO
Evaluating Protein Transfer Learning with TAPE
A Bayesian Theory of Conformity in Collective Decision Making OOO
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel OOO OOO
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation OOO
A Benchmark for Interpretability Methods in Deep Neural Networks OOO OOO OOO
Memory Efficient Adaptive Optimization OOO
Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions OOO
Convergence-Rate-Matching Discretization of Accelerated Optimization Flows Through Opportunistic State-Triggered Control OOO
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning OOO OOO OOO
Systematic generalization through meta sequence-to-sequence learning
Bayesian Joint Estimation of Multiple Graphical Models OOO OOO
Practical Two-Step Lookahead Bayesian Optimization OOO
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks OOO
Neural Jump Stochastic Differential Equations
Learning metrics for persistence-based summaries and applications for graph classification OOO OOO
ON THE VALUE OF TARGET SAMPLING IN COVARIATE-SHIFT
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization OOO
On Robustness of Principal Component Regression OOO
Meta Learning with Relational Information for Short Sequences
Residual Flows for Invertible Generative Modeling OOO OOO
Multi-Agent Common Knowledge Reinforcement Learning OOO
Learning to Learn By Self-Critique
Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes OOO OOO OOO
Neural Networks with Cheap Differential Operators OOO
Transductive Zero-Shot Learning with Visual Structure Constraint OOO
Dying Experts: Efficient Algorithms with Optimal Regret Bounds
Model similarity mitigates test set overuse
A unified theory for the origin of grid cells through the lens of pattern formation
On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons
Hierarchical Decision Making by Generating and Following Natural Language Instructions OOO OOO
SHE: A Fast and Accurate Deep Neural Network for Encrypted Data OOO
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond
A Game Theoretic Approach to Class-wise Selective Rationalization
Efficiently avoiding saddle points with zero order methods: No gradients required
Metamers of neural networks reveal divergence from human perceptual systems OOO
Spatial-Aware Feature Aggregation for Image based Cross-View Geo-Localization
Decentralized sketching of low rank matrices OOO
Average Case Column Subset Selection for Entrywise $\ell_1$-Norm Loss
Efficient Forward Architecture Search OOO
Unsupervised Meta Learning for Few-Show Image Classification OOO OOO
Learning Mixtures of Plackett-Luce Models from Structured Partial Orders
Certainty Equivalence is Efficient for Linear Quadratic Control
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models OOO
Logarithmic Regret for Online Control
Elliptical Perturbations for Differential Privacy
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks OOO OOO
KNG: The K-Norm Gradient Mechanism
CXPlain: Causal Explanations for Model Interpretation under Uncertainty OOO
Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning OOO
STREETS: A Novel Camera Network Dataset for Traffic Flow OOO OOO
Sequential Neural Processes
Policy Continuation with Hindsight Inverse Dynamics
Learning to Self-Train for Semi-Supervised Few-Shot Classification OOO OOO OOO
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations.
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization OOO
On the Expressive Power of Deep Polynomial Neural Networks OOO
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
Can SGD Learn Recurrent Neural Networks with Provable Generalization? OOO
Limits of Private Learning with Access to Public Data
Discrete Object Generation with Reversible Inductive Construction OOO
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models
Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards
Superset Technique for Approximate Recovery in One-Bit Compressed Sensing OOO
Bandits with Feedback Graphs and Switching Costs OOO
Functional Adversarial Attacks OOO
Statistical-Computational Tradeoff in Single Index Models
On Fenchel Mini-Max Learning
MarginGAN: Adversarial Training in Semi-Supervised Learning OOO OOO OOO
Poincar\'{e} Recurrence, Cycles and Spurious Equilibria in Gradient Descent for Non-Convex Non-Concave Zero-Sum Games
A unified variance-reduced accelerated gradient method for convex optimization OOO
Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin
Same-Cluster Querying for Overlapping Clusters OOO
Efficient Convex Relaxations for Streaming PCA
Learning Robust Global Representations by Penalizing Local Predictive Power OOO
Unsupervised Curricula for Visual Meta-Reinforcement Learning OOO OOO
Sample Complexity of Learning Mixture of Sparse Linear Regressions OOO
Large Scale Adversarial Representation Learning OOO OOO
G2SAT: Learning to Generate SAT Formulas
Neural Proximal Policy Optimization Attains Optimal Policy OOO
Dimensionality reduction: theoretical perspective on practical measures
Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback OOO
Multilabel reductions: what is my loss optimising?
Tight Sample Complexity of Learning One-hidden-layer Convolutional Neural Networks OOO
Deep Gamblers: Learning to Abstain with Portfolio Theory
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples OOO
Transfer Learning via Boosting to Minimize the Performance Gap Between Domains OOO
Splitting Steepest Descent for Progressive Training of Neural Networks OOO
Sequential Experimental Design for Transductive Linear Bandits
Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence OOO
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
Variational Graph Recurrent Neural Networks OOO OOO
Semi-Implicit Graph Variational Auto-Encoders OOO OOO
Unsupervised Learning of Object Keypoints for Perception and Control OOO
InteractiveRecGAN: a Model Based Reinforcement Learning Method with Adversarial Training for Online Recommendation OOO OOO OOO
Optimizing Generalized Rate Metrics through Three-player Games
Consistency-based Semi-supervised Learning for Object detection OOO OOO
Rates of Convergence for Large-scale Nearest Neighbor Classification OOO
An Embedding Framework for Consistent Polyhedral Surrogates OOO
Cross-Modal Learning with Adversarial Samples OOO
Fast PAC-Bayes via Shifted Rademacher Complexity OOO
Cell-Attention Reduces Vanishing Saliency of Recurrent Neural Networks OOO OOO
Program Synthesis and Semantic Parsing with Learned Code Idioms
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks OOO
High-Dimensional Optimization in Adaptive Random Subspaces OOO
Random Projections with Asymmetric Quantization
Superposition of many models into one
Private Testing of Distributions via Sample Permutations OOO
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds OOO
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets OOO
On Making Stochastic Classifiers Deterministic
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection OOO
Improving Black-box Adversarial Attacks with a Transfer-based Prior OOO
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks OOO OOO
Statistical Model Aggregation via Parameter Matching
On the (in)fidelity and sensitivity of explanations OOO
Exponential Family Estimation via Adversarial Dynamics Embedding OOO OOO
The Broad Optimality of Profile Maximum Likelihood
MintNet: Building Invertible Neural Networks with Masked Convolutions OOO
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
On Distributed Averaging for Stochastic k-PCA
Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation OOO OOO OOO
MaxGap Bandit: Adaptive Algorithms for Approximate Ranking
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting OOO
Online Forecasting of Total-Variation-bounded Sequences
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Dynamic Curriculum Learning by Gradient Descent
Unified Sample-Optimal Property Estimation in Near-Linear Time
Region Mutual Information Loss for Semantic Segmentation OOO
Learning Stable Deep Dynamics Models
Image Captioning: Transforming Objects into Words