
Csaba Szepesvári
Fellow & Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Fellow & Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Csaba Szepesvári works on reinforcement learning theory, creating and analyzing algorithms that learn efficiently and effectively while interacting with their environments in a sequential manner.
Csaba Szepesvári works on reinforcement learning theory, creating and analyzing algorithms that learn efficiently and effectively while interacting with their environments in a sequential manner. He is particularly interested in problems when a machine continuously interacts with its environment while trying to discover autonomously a good way of interacting with it. These interactive online learning problems are studied in various disciplines, such as within control theory under the name "dual control", or within machine learning itself in the area of reinforcement learning. Specific topics of research include computationally efficient and effective online learning and planning in large Markov Decision Processes, or with batch data; new algorithms for multicriteria reinforcement learning; efficient optimization and planning algorithms; and policy performance certificates.
Csaba is a Fellow and Canada CIFAR AI Chair at Amii and a Professor in the Computing Science Department of the University of Alberta. He is a Senior Staff Research Scientist at DeepMind in Edmonton, AB, leading the Foundations team. He is the Associate Editor of Mathematics of Operations Research and the Action Editor of the Journal of Machine Learning Research. Csaba is a Senior Member of the Institute of Electrical and Electronics Engineers and a member of the American Association for Artificial Intelligence. Csaba’s publications have received awards and accolades from top conferences such as the International Conference on Machine Learning (ICML), the Conference on Uncertainty in AI, and the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) where he received the Test of Time award in 2016. Csaba has co-authored more than 225 publications, including a book on Bandit Algorithms, which was released in the summer of 2020.
May 13th 2020
Research Post
Feb 19th 2020
Research Post
Jul 12th 2020
Research Post
Csaba has co-authored more than 225 publications, including a book on Bandit Algorithms, which was released in the summer of 2020.
Nov 23rd 2022
News
Amii researchers present their work in the fields of reinforcement learning, natural language processing, data optimization and more at the 2022 Conference on Neural Information Processing Systems.
Nov 30th 2021
News
Amii is proud to share the work of our researchers that will be presented at the thirty-fifth annual Neural Information Processing Systems (NeurIPS) conference, held online from December 6 - 14, 2021.
Oct 29th 2021
Research Post
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