Timezone: »
Author Information
Daniele Calandriello (INRIA Lille)
Alessandro Lazaric (Facebook AI Research)
Ioannis Koutis
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.
Related Events (a corresponding poster, oral, or spotlight)
-
2018 Oral: Improved large-scale graph learning through ridge spectral sparsification »
Thu Jul 12th 11:30 -- 11:50 AM Room K11
More from the Same Authors
-
2020 Poster: No-Regret Exploration in Goal-Oriented Reinforcement Learning »
Jean Tarbouriech · Evrard Garcelon · Michal Valko · Matteo Pirotta · Alessandro Lazaric -
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 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 A 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 A Healey · 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 »
Marc Abeille · Alessandro Lazaric -
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 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