An Efficient ε-BIC to BIC Transformation and Its Application to Black-Box Reduction in Revenue Maximization. - Yang Cai 001; Argyris Oikonomou; Grigoris Velegkas; Mingfei Zhao (CoRR, 2019)

How to Sell Information Optimally: An Algorithmic Study. - Yang Cai 001; Grigoris Velegkas (ITCS, 2021)

An Efficient ∊-BIC to BIC Transformation and Its Application to Black-Box Reduction in Revenue Maximization. - Yang Cai 001; Argyris Oikonomou; Grigoris Velegkas; Mingfei Zhao (SODA, 2021)

Universal Rates for Interactive Learning. - Steve Hanneke; Amin Karbasi; Shay Moran; Grigoris Velegkas (NeurIPS, 2022)

Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. - Alkis Kalavasis; Grigoris Velegkas; Amin Karbasi (NeurIPS, 2022)

Reinforcement Learning with Logarithmic Regret and Policy Switches. - Grigoris Velegkas; Zhuoran Yang; Amin Karbasi (NeurIPS, 2022)

Is Selling Complete Information (Approximately) Optimal? - Dirk Bergemann; Yang Cai 001; Grigoris Velegkas; Mingfei Zhao (EC, 2022)

The Best of Both Worlds: Reinforcement Learning with Logarithmic Regret and Policy Switches. - Grigoris Velegkas; Zhuoran Yang; Amin Karbasi (CoRR, 2022)

Reproducible Bandits. - Hossein Esfandiari; Alkis Kalavasis; Amin Karbasi; Andreas Krause 001; Vahab Mirrokni; Grigoris Velegkas (CoRR, 2022)

Replicable Bandits. - Hossein Esfandiari; Alkis Kalavasis; Amin Karbasi; Andreas Krause 001; Vahab Mirrokni; Grigoris Velegkas (ICLR, 2023)

Statistical Indistinguishability of Learning Algorithms. - Alkis Kalavasis; Amin Karbasi; Shay Moran; Grigoris Velegkas (ICML, 2023)

Optimal Learners for Realizable Regression: PAC Learning and Online Learning. - Idan Attias; Steve Hanneke; Alkis Kalavasis; Amin Karbasi; Grigoris Velegkas (NeurIPS, 2023)

Replicable Clustering. - Hossein Esfandiari; Amin Karbasi; Vahab Mirrokni; Grigoris Velegkas; Felix Zhou 002 (NeurIPS, 2023)

Replicability in Reinforcement Learning. - Amin Karbasi; Grigoris Velegkas; Lin Yang 011; Felix Zhou 002 (NeurIPS, 2023)

Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. - Idan Attias; Steve Hanneke; Alkis Kalavasis; Amin Karbasi; Grigoris Velegkas (COLT, 2024)

Replicable Learning of Large-Margin Halfspaces. - Alkis Kalavasis; Amin Karbasi; Kasper Green Larsen; Grigoris Velegkas; Felix Zhou 002 (ICML, 2024)

Randomized Truthful Auctions with Learning Agents. - Gagan Aggarwal; Anupam Gupta 001; Andrés Perlroth; Grigoris Velegkas (NeurIPS, 2024)

Universal Rates for Active Learning. - Steve Hanneke; Amin Karbasi; Shay Moran; Grigoris Velegkas (NeurIPS, 2024)

Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models. - Alkis Kalavasis; Amin Karbasi; Argyris Oikonomou; Katerina Sotiraki; Grigoris Velegkas; Manolis Zampetakis (NeurIPS, 2024)

On the Computational Landscape of Replicable Learning. - Alkis Kalavasis; Amin Karbasi; Grigoris Velegkas; Felix Zhou 002 (NeurIPS, 2024)

User Response in Ad Auctions: An MDP Formulation of Long-term Revenue Optimization. - Yang Cai 001; Zhe Feng 004; Christopher Liaw; Aranyak Mehta; Grigoris Velegkas (WWW, 2024)

Pointwise Lipschitz Continuous Graph Algorithms via Proximal Gradient Analysis. - Quanquan C. Liu; Grigoris Velegkas; Yuichi Yoshida; Felix Zhou 002 (CoRR, 2024)

Injecting Undetectable Backdoors in Deep Learning and Language Models. - Alkis Kalavasis; Amin Karbasi; Argyris Oikonomou; Katerina Sotiraki; Grigoris Velegkas; Manolis Zampetakis (CoRR, 2024)

Procurement Auctions via Approximately Optimal Submodular Optimization. - Yuan Deng; Amin Karbasi; Vahab Mirrokni; Renato Paes Leme; Grigoris Velegkas; Song Zuo (CoRR, 2024)

Characterizations of Language Generation With Breadth. - Alkis Kalavasis; Anay Mehrotra; Grigoris Velegkas (CoRR, 2024)

Understanding Aggregations of Proper Learners in Multiclass Classification. - Julian Asilis; Mikael Møller Høgsgaard; Grigoris Velegkas (ALT, 2025)

On the Limits of Language Generation: Trade-Offs between Hallucination and Mode-Collapse. - Alkis Kalavasis; Anay Mehrotra; Grigoris Velegkas (STOC, 2025)

On Agnostic PAC Learning in the Small Error Regime. - Julian Asilis; Mikael Møller Høgsgaard; Grigoris Velegkas (CoRR, 2025)

(Im)possibility of Automated Hallucination Detection in Large Language Models. - Amin Karbasi; Omar Montasser; John Sous; Grigoris Velegkas (CoRR, 2025)

On Union-Closedness of Language Generation. - Steve Hanneke; Amin Karbasi; Anay Mehrotra; Grigoris Velegkas (CoRR, 2025)