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Author Information
Yasin Abbasi Yadkori (Adobe Research)
Peter Bartlett (UC Berkeley)

Peter Bartlett is professor of Computer Science and Statistics at the University of California at Berkeley, Associate Director of the Simons Institute for the Theory of Computing, and Director of the Foundations of Data Science Institute. He has previously held positions at the Queensland University of Technology, the Australian National University and the University of Queensland. His research interests include machine learning and statistical learning theory, and he is the co-author of the book Neural Network Learning: Theoretical Foundations. He has been Institute of Mathematical Statistics Medallion Lecturer, winner of the Malcolm McIntosh Prize for Physical Scientist of the Year, and Australian Laureate Fellow, and he is a Fellow of the IMS, Fellow of the ACM, and Fellow of the Australian Academy of Science.
Victor Gabillon (QUT - ACEMS)
More from the Same Authors
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2021 Invited Talk: Benign Overfitting »
Peter Bartlett -
2020 Poster: Model Selection in Contextual Stochastic Bandit Problems »
Aldo Pacchiano · My Phan · Yasin Abbasi Yadkori · Anup Rao · Julian Zimmert · Tor Lattimore · Csaba Szepesvari -
2019 Poster: Thompson Sampling and Approximate Inference »
My Phan · Yasin Abbasi Yadkori · Justin Domke -
2019 Poster: Bootstrapping Upper Confidence Bound »
Botao Hao · Yasin Abbasi Yadkori · Zheng Wen · Guang Cheng -
2018 Poster: Scalar Posterior Sampling with Applications »
Georgios Theocharous · Zheng Wen · Yasin Abbasi Yadkori · Nikos Vlassis -
2017 Poster: Conservative Contextual Linear Bandits »
Abbas Kazerouni · Mohammad Ghavamzadeh · Yasin Abbasi · Benjamin Van Roy -
2017 Poster: Spectrally-normalized margin bounds for neural networks »
Peter Bartlett · Dylan J Foster · Matus Telgarsky -
2017 Spotlight: Spectrally-normalized margin bounds for neural networks »
Peter Bartlett · Dylan J Foster · Matus Telgarsky -
2017 Poster: Alternating minimization for dictionary learning with random initialization »
Niladri Chatterji · Peter Bartlett -
2017 Poster: Acceleration and Averaging in Stochastic Descent Dynamics »
Walid Krichene · Peter Bartlett -
2017 Spotlight: Acceleration and Averaging in Stochastic Descent Dynamics »
Walid Krichene · Peter Bartlett -
2015 Workshop: Machine Learning From and For Adaptive User Technologies: From Active Learning & Experimentation to Optimization & Personalization »
Joseph Jay Williams · Yasin Abbasi Yadkori · Finale Doshi-Velez -
2015 Poster: Minimax Time Series Prediction »
Wouter Koolen · Alan Malek · Peter Bartlett · Yasin Abbasi Yadkori -
2014 Workshop: Large-scale reinforcement learning and Markov decision problems »
Benjamin Van Roy · Mohammad Ghavamzadeh · Peter Bartlett · Yasin Abbasi Yadkori · Ambuj Tewari -
2013 Workshop: Resource-Efficient Machine Learning »
Yevgeny Seldin · Yasin Abbasi Yadkori · Yacov Crammer · Ralf Herbrich · Peter Bartlett -
2013 Poster: Approximate Dynamic Programming Finally Performs Well in the Game of Tetris »
Victor Gabillon · Mohammad Ghavamzadeh · Bruno Scherrer -
2013 Poster: Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions »
Yasin Abbasi Yadkori · Peter Bartlett · Varun Kanade · Yevgeny Seldin · Csaba Szepesvari -
2013 Poster: Adaptive Submodular Maximization in Bandit Setting »
Victor Gabillon · Branislav Kveton · Zheng Wen · Brian Eriksson · S. Muthukrishnan -
2012 Poster: Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence »
Victor Gabillon · Mohammad Ghavamzadeh · Alessandro Lazaric -
2011 Poster: Improved Algorithms for Linear Stochastic Bandits »
Yasin Abbasi Yadkori · David Pal · Csaba Szepesvari -
2011 Spotlight: Improved Algorithms for Linear Stochastic Bandits »
Yasin Abbasi Yadkori · David Pal · Csaba Szepesvari -
2011 Poster: Multi-Bandit Best Arm Identification »
Victor Gabillon · Mohammad Ghavamzadeh · Alessandro Lazaric · Sebastien Bubeck