Grigoris Velegkas

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 27

Top Topics

Penalized Likelihood

Expected Reward

Top Venues

Publications

Yang Cai, Zhe Feng, Christopher Liaw, Aranyak Mehta, Grigoris Velegkas
User Response in Ad Auctions: An MDP Formulation of Long-term Revenue Optimization. WWW (2024)
Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou
On the Computational Landscape of Replicable Learning. CoRR (2024)
Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis
Injecting Undetectable Backdoors in Deep Learning and Language Models. CoRR (2024)
Quanquan C. Liu, Grigoris Velegkas, Yuichi Yoshida, Felix Zhou
Pointwise Lipschitz Continuous Graph Algorithms via Proximal Gradient Analysis. CoRR (2024)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. COLT (2024)
Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou
Replicable Learning of Large-Margin Halfspaces. CoRR (2024)
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
Statistical Indistinguishability of Learning Algorithms. CoRR (2023)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. NeurIPS (2023)
Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou
Replicable Clustering. CoRR (2023)
Amin Karbasi, Grigoris Velegkas, Lin F. Yang, Felix Zhou
Replicability in Reinforcement Learning. CoRR (2023)
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
Statistical Indistinguishability of Learning Algorithms. ICML (2023)
Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou
Replicable Clustering. NeurIPS (2023)
Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
Replicable Bandits. ICLR (2023)
Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou
Replicability in Reinforcement Learning. NeurIPS (2023)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. CoRR (2023)
Dirk Bergemann, Yang Cai, Grigoris Velegkas, Mingfei Zhao
Is Selling Complete Information (Approximately) Optimal? CoRR (2022)
Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas
Universal Rates for Interactive Learning. NeurIPS (2022)
Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
Reproducible Bandits. CoRR (2022)
Grigoris Velegkas, Zhuoran Yang, Amin Karbasi
The Best of Both Worlds: Reinforcement Learning with Logarithmic Regret and Policy Switches. CoRR (2022)
Dirk Bergemann, Yang Cai, Grigoris Velegkas, Mingfei Zhao
Is Selling Complete Information (Approximately) Optimal? EC (2022)
Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. CoRR (2022)
Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. NeurIPS (2022)
Grigoris Velegkas, Zhuoran Yang, Amin Karbasi
Reinforcement Learning with Logarithmic Regret and Policy Switches. NeurIPS (2022)
Yang Cai, Argyris Oikonomou, Grigoris Velegkas, Mingfei Zhao
-BIC to BIC Transformation and Its Application to Black-Box Reduction in Revenue Maximization. SODA (2021)
Yang Cai, Grigoris Velegkas
How to Sell Information Optimally: An Algorithmic Study. ITCS (2021)
Yang Cai, Grigoris Velegkas
How to Sell Information Optimally: an Algorithmic Study. CoRR (2020)
Yang Cai, Argyris Oikonomou, Grigoris Velegkas, Mingfei Zhao
An Efficient ε-BIC to BIC Transformation and Its Application to Black-Box Reduction in Revenue Maximization. CoRR (2019)