Antonakopoulos, Kimon

23 publications

TMLR 2026 Multi-Step Alignment as Markov Games: An Optimistic Online Mirror Descent Approach with Convergence Guarantees Yongtao Wu, Luca Viano, Kimon Antonakopoulos, Yihang Chen, Zhenyu Zhu, Quanquan Gu, Volkan Cevher

NeurIPS 2025 Generalized Gradient Norm Clipping & Non-Euclidean $(L_0,L_1)$-Smoothness Thomas Pethick, Wanyun Xie, Mete Erdogan, Kimon Antonakopoulos, Tony Silveti-Falls, Volkan Cevher

ICML 2025 Layer-Wise Quantization for Quantized Optimistic Dual Averaging Anh Duc Nguyen, Ilia Markov, Zhengqing Wu, Ali Ramezani-Kebrya, Kimon Antonakopoulos, Dan Alistarh, Volkan Cevher

ICML 2025 Training Deep Learning Models with Norm-Constrained LMOs Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos, Zhenyu Zhu, Antonio Silveti-Falls, Volkan Cevher

ICLR 2024 Advancing the Lower Bounds: An Accelerated, Stochastic, Second-Order Method with Optimal Adaptation to Inexactness Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov, Ali Kavis, Kimon Antonakopoulos, Volkan Cevher, Martin Takáč

NeurIPSW 2024 Extra-Gradient and Optimistic Gradient Descent Converge in Iterates Faster than $O(1/\sqrt{T})$ in All Monotone Lipschitz Variational Inequalities Kimon Antonakopoulos

ICML 2024 Improving SAM Requires Rethinking Its Optimization Formulation Wanyun Xie, Fabian Latorre, Kimon Antonakopoulos, Thomas Pethick, Volkan Cevher

NeurIPSW 2024 Layer-Wise Quantization for Distributed Variational Inequalities Anh Duc Nguyen, Ilia Markov, Ali Ramezani-Kebrya, Kimon Antonakopoulos, Dan Alistarh, Volkan Cevher

JMLR 2024 On the Generalization of Stochastic Gradient Descent with Momentum Ali Ramezani-Kebrya, Kimon Antonakopoulos, Volkan Cevher, Ashish Khisti, Ben Liang

ICML 2024 Universal Gradient Methods for Stochastic Convex Optimization Anton Rodomanov, Ali Kavis, Yongtao Wu, Kimon Antonakopoulos, Volkan Cevher

ICLR 2023 Distributed Extra-Gradient with Optimal Complexity and Communication Guarantees Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher

ICML 2022 AdaGrad Avoids Saddle Points Kimon Antonakopoulos, Panayotis Mertikopoulos, Georgios Piliouras, Xiao Wang

NeurIPS 2022 Adaptive Stochastic Variance Reduction for Non-Convex Finite-Sum Minimization Ali Kavis, Stratis Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher

NeurIPS 2022 Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods Kimon Antonakopoulos, Ali Kavis, Volkan Cevher

NeurIPS 2022 No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity via Learning Rate Separation Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos

ICML 2022 UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees Kimon Antonakopoulos, Dong Quan Vu, Volkan Cevher, Kfir Levy, Panayotis Mertikopoulos

ICLR 2021 Adaptive Extra-Gradient Methods for Min-Max Optimization and Games Kimon Antonakopoulos, Veronica Belmega, Panayotis Mertikopoulos

NeurIPS 2021 Adaptive First-Order Methods Revisited: Convex Minimization Without Lipschitz Requirements Kimon Antonakopoulos, Panayotis Mertikopoulos

COLT 2021 Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium Yu-Guan Hsieh, Kimon Antonakopoulos, Panayotis Mertikopoulos

NeurIPS 2021 Fast Routing Under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights Dong Quan Vu, Kimon Antonakopoulos, Panayotis Mertikopoulos

NeurIPS 2021 Sifting Through the Noise: Universal First-Order Methods for Stochastic Variational Inequalities Kimon Antonakopoulos, Thomas Pethick, Ali Kavis, Panayotis Mertikopoulos, Volkan Cevher

ICLR 2020 Online and Stochastic Optimization Beyond Lipschitz Continuity: A Riemannian Approach Kimon Antonakopoulos, E. Veronica Belmega, Panayotis Mertikopoulos

NeurIPS 2019 An Adaptive Mirror-Prox Method for Variational Inequalities with Singular Operators Kimon Antonakopoulos, Veronica Belmega, Panayotis Mertikopoulos