Scholar
Luca Viano
Google Scholar ID: E_dAUKEAAAAJ
EPFL
reinforcement learning
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Citations & Impact
All-time
Citations
187
H-index
7
i10-index
6
Publications
20
Co-authors
27
list available
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Publications
10 items
Multi-agent imitation learning with function approximation: Linear Markov games and beyond
2026
Cited
0
Provably avoiding over-optimization in Direct Preference Optimization without knowing the data distribution
2026
Cited
0
Direct Preference Optimization with Rating Information: Practical Algorithms and Provable Gains
2026
Cited
1
Rate optimal learning of equilibria from data
2025
Cited
0
Inverse Q-Learning Done Right: Offline Imitation Learning in $Q^pi$-Realizable MDPs
2025
Cited
0
Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning
2025
Cited
0
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
2025
Cited
0
Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning
2025
Cited
0
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Resume (English only)
Academic Achievements
Multiple papers accepted at top-tier conferences including ICML, COLT, NeurIPS, and WINE.
COLT 2025 paper with Antoine and Gergo.
Two ICML 2025 acceptances: one on interactive imitation learning in Markov Games, another on the SOAR algorithm.
ICML 2024 paper on imitation learning that removes an unrealistic assumption from prior work.
NeurIPS 2023 Spotlight award for work that beats a classic lower bound via a simple modification to online learning.
Several arXiv preprints on offline imitation learning, online learning with bandit feedback, and RLHF (Reinforcement Learning from Human Feedback).
June 2025 breakthrough: offline imitation learning without policy realizability in Q^pi-realizable MDPs (with Antoine and Gergo).
Research Experience
Worked as a Data Scientist at Datapred.
Starting a summer internship at Amazon, Sunnyvale, California in June 2025.
Co-organizing the Virtual RL Theory Seminars.
Co-organized the Multi Agent RL Summer School in August 2024.
Visited Gergely Neu in Barcelona for four months (Sep 2023–Jan 2024) under ELLIS support.
Co-authors
27 total
Volkan Cevher
Associate Professor, LIONS, EPFL. Amazon Scholar (AGI Foundations).
Stratis Skoulakis
Aarhus University
Parameswaran Kamalaruban
Visa
Adrian Weller
Director of Research, Machine Learning, University of Cambridge
Gergely Neu
Artificial Intelligence and Machine Learning group, Universitat Pompeu Fabra
Fanghui Liu
Assistant Professor, University of Warwick
Ahmet Alacaoglu
University of British Columbia
Niao He
Associate Professor, ETH Zürich
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