Biography

I am a second-year Ph.D. Student at Criteo AI Lab and ENSAE-CREST, under the supervision of Anna Korba, Victor-Emmanuel Brunel and David Rohde. Previously, I was an Applied Scientist at Amazon and a Scholar at Google DeepMind. I am mainly focusing on designing and analyzing practical reward-optimizing algorithms for interactive systems. Precisely, I am interested in Off-Policy Evaluation and Learning, Practical Bandit Algorithms, Bayesian Analysis and Learning, Recommender Systems, and Generative Models.

Publications

2024

• Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning. Neurips 2024 (Spotlight, Top 2%) and RecSys 2024 CONSEQUENCES Workshop (Oral)
  Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin

• Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling. UAI 2024 (Poster)
  Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

• Bayesian Off-Policy Evaluation and Learning for Large Action Spaces. Preprint
  Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

• Diffusion Models Meet Contextual Bandits with Large Action Spaces. Preprint
  Imad Aouali

• Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits. Preprint
  Nicolas Nguyen*, Imad Aouali*, András György, Claire Vernade
  (*Equal contribution)

2023

• Linear Diffusion Models Meet Contextual Bandits With Large Action Spaces. Foundation Models for Decision Making Workshop at NeurIPS 2023
  Imad Aouali

• Exponential Smoothing for Off-Policy Learning. ICML  2023 (Oral & Poster, Top 2%)
  Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

• Mixed-Effect Thompson Sampling. AISTATS  2023  (Poster)
  Imad Aouali, Branislav Kveton, Sumeet Katariya

• Probabilistic Rank and Reward: A Scalable Model for Slate Recommendation. Preprint
  Imad Aouali*, Achraf Ait Sidi Hammou*, Sergey Ivanov, Otmane Sakhi, David Rohde, Flavian Vasile (*Equal contribution)

2022

• Reward Optimizing Recommendation using Deep Learning and Fast Maximum Inner Product Search. Tutorials at KDD 2022 and ECML 2022
  Imad Aouali, Amine Benhalloum, Martin Bompaire, Achraf Ait Sidi Hammou, Sergey Ivanov, Benjamin Heymann, David Rohde, Otmane Sakhi, Flavian Vasile, Maxime Vono (All authors contributed equally)

• Combining Reward and Rank Signals for Slate Recommendation. BCIRWIS Workshop at KDD 2022
  Imad Aouali, Sergey Ivanov, Mike Gartrell, David Rohde, Flavian Vasile, Victor Zaytsev, Diego Legrand

• Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of Simulation. SimuRec Workshop at RecSys 2022 (Position Paper)
  Imad Aouali, Amine Benhalloum, Martin Bompaire, Benjamin Heymann, Olivier Jeunen, David Rohde, Otmane Sakhi, Flavian Vasile (All authors contributed equally)