Angeliki Giannou

19 papers A* 8A 2Journal 9

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition. ICML Zheyang Xiong, Ziyang Cai, John Cooper, Albert Ge, Vasilis Papageorgiou, Zack Sifakis, Angeliki Giannou, Ziqian Lin, Liu Yang, Saurabh Agarwal, Grigorios Chrysos, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos
2025	A	`conf`	How Well Can Transformers Emulate In-Context Newton's Method? AISTATS Angeliki Giannou, Liu Yang, Tianhao Wang, Dimitris Papailiopoulos, Jason D. Lee
2024	A*	`conf`	Accelerated Regularized Learning in Finite N-Person Games. NeurIPS Kyriakos Lotidis, Angeliki Giannou, Panayotis Mertikopoulos, Nicholas Bambos
2024	J	`jnl`	Accelerated regularized learning in finite N-person games. CoRR Kyriakos Lotidis, Angeliki Giannou, Panayotis Mertikopoulos, Nicholas Bambos
2024	J	`jnl`	Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition. CoRR Zheyang Xiong, Ziyang Cai, John Cooper, Albert Ge, Vasilis Papageorgiou, Zack Sifakis, Angeliki Giannou, Ziqian Lin, Liu Yang, Saurabh Agarwal, Grigorios G. Chrysos, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos
2024	J	`jnl`	How Well Can Transformers Emulate In-context Newton's Method? CoRR Angeliki Giannou, Liu Yang, Tianhao Wang, Dimitris Papailiopoulos, Jason D. Lee
2024	A	`conf`	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements. AISTATS Emmanouil-Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie
2023	J	`jnl`	Dissecting Chain-of-Thought: A Study on Compositional In-Context Learning of MLPs. CoRR Yingcong Li, Kartik Sreenivasan, Angeliki Giannou, Dimitris S. Papailiopoulos, Samet Oymak
2023	A*	`conf`	Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning. NeurIPS Yingcong Li, Kartik Sreenivasan, Angeliki Giannou, Dimitris Papailiopoulos, Samet Oymak
2023	A*	`conf`	Looped Transformers as Programmable Computers. ICML Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris Papailiopoulos
2023	J	`jnl`	Looped Transformers as Programmable Computers. CoRR Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris S. Papailiopoulos
2023	J	`jnl`	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements. CoRR Emmanouil V. Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie
2023	J	`jnl`	The Expressive Power of Tuning Only the Norm Layers. CoRR Angeliki Giannou, Shashank Rajput, Dimitris S. Papailiopoulos
2023	A*	`conf`	The Expressive Power of Tuning Only the Normalization Layers. COLT Angeliki Giannou, Shashank Rajput, Dimitris Papailiopoulos
2022	A*	`conf`	On the convergence of policy gradient methods to Nash equilibria in general stochastic games. NeurIPS Angeliki Giannou, Kyriakos Lotidis, Panayotis Mertikopoulos, Emmanouil V. Vlatakis-Gkaragkounis
2022	J	`jnl`	On the convergence of policy gradient methods to Nash equilibria in general stochastic games. CoRR Angeliki Giannou, Kyriakos Lotidis, Panayotis Mertikopoulos, Emmanouil V. Vlatakis-Gkaragkounis
2021	J	`jnl`	From Learning with Partial Information to Bandits: Only Strict Nash Equilibria are Stable. CoRR Angeliki Giannou, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos
2021	A*	`conf`	Survival of the strictest: Stable and unstable equilibria under regularized learning with partial information. COLT Angeliki Giannou, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos
2021	A*	`conf`	The convergence rate of regularized learning in games: From bandits and uncertainty to optimism and beyond. NeurIPS Angeliki Giannou, Emmanouil V. Vlatakis-Gkaragkounis, Panayotis Mertikopoulos