DeLTA Lab: Denmark Learning Theory and Applications
We are a research group affiliated with the Department of Computer Science at the University of Copenhagen (DIKU) studying diverse aspects of Machine Learning Theory and its applications, including, but not limited to Reinforcement Learning, Online Learning and Bandits, PAC-Bayesian analysis.
Members
Professor, DIKU
Assistant Professor, DIKU
Professor, DIKU
Saeed Masoudian
Postdoc, DIKU
Ph.D. Student, DIKU
Hippolyte Bourel
Ph.D. Student, DIKU
Ola Rønning
Postdoc, DIKU
Julian Zimmert
Research Scientist, Google Research
DeLTA Seminar
You can subscribe to the DeLTA Seminar mailing list here or by sending an empty email to delta-seminar-join@list.ku.dk.
New Publications
Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo. No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions, NeurIPS 2023. [arXiv]
Hippolyte Bourel, Anders Jonsson, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi. Exploration in Reward Machines with Low Regret, AISTATS 2023. [plmr]
Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin. A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs. NeurIPS, 2022. [arXiv]
Saeed Masoudian, Julian Zimmert, Yevgeny Seldin. A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback. NeurIPS 2022. [arXiv]
Yi-Shan Wu, Yevgeny Seldin. Split-kl and PAC-Bayes-split-kl Inequalities. NeurIPS, 2022. [arXiv]
Nikolaos Nomikos, Mohammad Sadegh Talebi, Themistoklis Charalambous, Risto Wichman. Bandit-based power control in full-duplex cooperative relay networks with strict-sense stationary and non-stationary wireless communication channels. IEEE Open Journal of the Communications Society 3: 366-378, 2022. [doi]
Courses
We offer several Machine Learning courses at the University of Copenhagen.
Alumni
Yunlian Lyu
Ph.D. Student