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  • Criteo AI Lab | CREST | Centrale | ENS
  • Paris, France

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  1. offpolicy_ls offpolicy_ls Public

    Source code for the paper "Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning" published at NeuRIPS '24.

    Python 4 1

  2. fopo fopo Public

    Source code for the paper "Fast Offline Policy Optimization for Large Scale Recommendation" published at the Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23).

    Python 2

  3. criteo-research/blob criteo-research/blob Public

    Source code for our paper "BLOB: a probabilistic model for recommendation that combines organic and bandit signals" published at KDD 2020.

    Python 16 10

  4. Reward-Optimizing-Reco Reward-Optimizing-Reco Public

    Materials for the "Reward Optimising Recommendation using Deep Learning and Fast Maximum Inner Product Search" tutorial delivered at the 28th SIGKDD Conference on Knowledge Discovery and Data Minin…

    Jupyter Notebook 5 2

  5. olivierjeunen/decision-theory-www-2021 olivierjeunen/decision-theory-www-2021 Public

    Materials for the "Recommender Systems through the lens of Decision Theory" tutorial delivered at the 30th Web Conference (WWW '21).

    Jupyter Notebook 11 1

  6. sadeqa/Super-Mario-Bros-RL sadeqa/Super-Mario-Bros-RL Public

    This project explores deep reinforcement learning, hybrid actor-critic approach with A3C/PPO combined with curiosity for playing Super Mario Bros

    Jupyter Notebook 79 15