Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Matrix and Tensor Completion for Background Model Initialization

Predict scores of NBA games using regularized matrix completion

Data Science and Matrix Optimization course

Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.

MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3

Lightweight Python library for in-memory matrix completion.

Matlab library for gradient descent algorithms: Version 1.0.1

Imputation method for scRNA-seq based on low-rank approximation

Code for Graph Convolutional Matrix Factorization for Bipartite Edge Prediction

Factor-Based Imputation for Missing Data

[Tool] Low rank matrix recovery by minimizing matrix norm

OnLine Low-rank Subspace tracking by TEnsor CP Decomposition in Matlab: Version 1.0.1

[ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

A visual complexity dataset across seven different categories, including Scenes, Advertisements, Visualization and infographics, Objects, Interior design, Art, and Suprematism for computer vision application.

[ICLR 2020, Oral] Harnessing Structures for Value-Based Planning and Reinforcement Learning

A fast and accurate deconvolution algorithm based on regularized matrix completion algorithm (ENIGMA)

Source code for the paper "Extendable Neural Matrix Completion"

Low-rank Matrix Completion using Alternating Minimization