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Author Information
Jean Tarbouriech (Facebook AI Research & Inria)
Evrard Garcelon (Facebook AI Research and ENSAE)
Michal Valko (DeepMind)
Michal is a research scientist in DeepMind Paris and SequeL team at Inria Lille - Nord Europe, France, lead by Philippe Preux and Rémi Munos. He also teaches the course Graphs in Machine Learning at l'ENS Cachan. Michal is primarily interested in designing algorithms that would require as little human supervision as possible. This means 1) reducing the “intelligence” that humans need to input into the system and 2) minimising the data that humans need spend inspecting, classifying, or “tuning” the algorithms. Another important feature of machine learning algorithms should be the ability to adapt to changing environments. That is why he is working in domains that are able to deal with minimal feedback, such as bandit algorithms, semi-supervised learning, and anomaly detection. Most recently he has worked on sequential algorithms with structured decisions where exploiting the structure can lead to provably faster learning. In the past the common thread of Michal's work has been adaptive graph-based learning and its application to the real world applications such as recommender systems, medical error detection, and face recognition. His industrial collaborators include Adobe, Intel, Technicolor, and Microsoft Research. He received his PhD in 2011 from University of Pittsburgh under the supervision of Miloš Hauskrecht and after was a postdoc of Rémi Munos.
Matteo Pirotta (Facebook AI Research)
Alessandro Lazaric (Facebook AI Research)
More from the Same Authors
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2021 : Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection »
Matteo Papini · Andrea Tirinzoni · Aldo Pacchiano · Marcello Restelli · Alessandro Lazaric · Matteo Pirotta -
2021 : A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs »
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2021 : Bridging The Gap between Local and Joint Differential Privacy in RL »
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2021 : Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret »
Jean Tarbouriech · Jean Tarbouriech · Simon Du · Matteo Pirotta · Michal Valko · Alessandro Lazaric -
2021 : A general sample complexity analysis of vanilla policy gradient »
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2021 : Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching »
Pierre-Alexandre Kamienny · Jean Tarbouriech · Alessandro Lazaric · Ludovic Denoyer -
2021 : Exploration-Driven Representation Learning in Reinforcement Learning »
Akram Erraqabi · Mingde Zhao · Marlos C. Machado · Yoshua Bengio · Sainbayar Sukhbaatar · Ludovic Denoyer · Alessandro Lazaric -
2023 Poster: Layered State Discovery for Incremental Autonomous Exploration »
Liyu Chen · Andrea Tirinzoni · Alessandro Lazaric · Matteo Pirotta -
2022 Workshop: Responsible Decision Making in Dynamic Environments »
Virginie Do · Thorsten Joachims · Alessandro Lazaric · Joelle Pineau · Matteo Pirotta · Harsh Satija · Nicolas Usunier -
2022 Poster: Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times »
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2022 Spotlight: Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times »
Daniele Calandriello · Luigi Carratino · Alessandro Lazaric · Michal Valko · Lorenzo Rosasco -
2021 : Invited Talk by Alessandro Lazaric »
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2021 Poster: Leveraging Good Representations in Linear Contextual Bandits »
Matteo Papini · Andrea Tirinzoni · Marcello Restelli · Alessandro Lazaric · Matteo Pirotta -
2021 Spotlight: Leveraging Good Representations in Linear Contextual Bandits »
Matteo Papini · Andrea Tirinzoni · Marcello Restelli · Alessandro Lazaric · Matteo Pirotta -
2021 Poster: Kernel-Based Reinforcement Learning: A Finite-Time Analysis »
Omar Darwiche Domingues · Pierre Menard · Matteo Pirotta · Emilie Kaufmann · Michal Valko -
2021 Spotlight: Kernel-Based Reinforcement Learning: A Finite-Time Analysis »
Omar Darwiche Domingues · Pierre Menard · Matteo Pirotta · Emilie Kaufmann · Michal Valko -
2021 Poster: Reinforcement Learning with Prototypical Representations »
Denis Yarats · Rob Fergus · Alessandro Lazaric · Lerrel Pinto -
2021 Spotlight: Reinforcement Learning with Prototypical Representations »
Denis Yarats · Rob Fergus · Alessandro Lazaric · Lerrel Pinto -
2020 Poster: Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation »
Marc Abeille · Alessandro Lazaric -
2020 Poster: Learning Near Optimal Policies with Low Inherent Bellman Error »
Andrea Zanette · Alessandro Lazaric · Mykel Kochenderfer · Emma Brunskill -
2020 Poster: Meta-learning with Stochastic Linear Bandits »
Leonardo Cella · Alessandro Lazaric · Massimiliano Pontil -
2020 Poster: Near-linear time Gaussian process optimization with adaptive batching and resparsification »
Daniele Calandriello · Luigi Carratino · Alessandro Lazaric · Michal Valko · Lorenzo Rosasco -
2019 : Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret »
Michal Valko -
2019 : Michal Valko: How Negative Dependence Broke the Quadratic Barrier for Learning with Graphs and Kernels »
Michal Valko -
2019 : Poster Session 1 (all papers) »
Matilde Gargiani · Yochai Zur · Chaim Baskin · Evgenii Zheltonozhskii · Liam Li · Ameet Talwalkar · Xuedong Shang · Harkirat Singh Behl · Atilim Gunes Baydin · Ivo Couckuyt · Tom Dhaene · Chieh Lin · Wei Wei · Min Sun · Orchid Majumder · Michele Donini · Yoshihiko Ozaki · Ryan P. Adams · Christian Geißler · Ping Luo · zhanglin peng · · Ruimao Zhang · John Langford · Rich Caruana · Debadeepta Dey · Charles Weill · Xavi Gonzalvo · Scott Yang · Scott Yak · Eugen Hotaj · Vladimir Macko · Mehryar Mohri · Corinna Cortes · Stefan Webb · Jonathan Chen · Martin Jankowiak · Noah Goodman · Aaron Klein · Frank Hutter · Mojan Javaheripi · Mohammad Samragh · Sungbin Lim · Taesup Kim · SUNGWOONG KIM · Michael Volpp · Iddo Drori · Yamuna Krishnamurthy · Kyunghyun Cho · Stanislaw Jastrzebski · Quentin de Laroussilhe · Mingxing Tan · Xiao Ma · Neil Houlsby · Andrea Gesmundo · Zalán Borsos · Krzysztof Maziarz · Felipe Petroski Such · Joel Lehman · Kenneth Stanley · Jeff Clune · Pieter Gijsbers · Joaquin Vanschoren · Felix Mohr · Eyke Hüllermeier · Zheng Xiong · Wenpeng Zhang · Wenwu Zhu · Weijia Shao · Aleksandra Faust · Michal Valko · Michael Y Li · Hugo Jair Escalante · Marcel Wever · Andrey Khorlin · Tara Javidi · Anthony Francis · Saurajit Mukherjee · Jungtaek Kim · Michael McCourt · Saehoon Kim · Tackgeun You · Seungjin Choi · Nicolas Knudde · Alexander Tornede · Ghassen Jerfel -
2019 Poster: Exploiting structure of uncertainty for efficient matroid semi-bandits »
Pierre Perrault · Vianney Perchet · Michal Valko -
2019 Poster: Scale-free adaptive planning for deterministic dynamics & discounted rewards »
Peter Bartlett · Victor Gabillon · Jennifer Healey · Michal Valko -
2019 Oral: Exploiting structure of uncertainty for efficient matroid semi-bandits »
Pierre Perrault · Vianney Perchet · Michal Valko -
2019 Oral: Scale-free adaptive planning for deterministic dynamics & discounted rewards »
Peter Bartlett · Victor Gabillon · Jennifer Healey · Michal Valko -
2018 Poster: Improved large-scale graph learning through ridge spectral sparsification »
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko -
2018 Oral: Improved large-scale graph learning through ridge spectral sparsification »
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko -
2018 Poster: Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning »
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Ronald Ortner -
2018 Poster: Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems »
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2018 Oral: Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems »
Marc Abeille · Alessandro Lazaric -
2018 Oral: Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning »
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Ronald Ortner -
2017 : Faster graph bandit learning using information about the neighbors »
Michal Valko -
2017 Poster: Zonotope hit-and-run for efficient sampling from projection DPPs »
Guillaume Gautier · Rémi Bardenet · Michal Valko -
2017 Talk: Zonotope hit-and-run for efficient sampling from projection DPPs »
Guillaume Gautier · Rémi Bardenet · Michal Valko -
2017 Poster: Second-Order Kernel Online Convex Optimization with Adaptive Sketching »
Daniele Calandriello · Alessandro Lazaric · Michal Valko -
2017 Talk: Second-Order Kernel Online Convex Optimization with Adaptive Sketching »
Daniele Calandriello · Alessandro Lazaric · Michal Valko