Diakonikolas, Jelena

29 publications

ICLR 2025 Last Iterate Convergence of Incremental Methods as a Model of Forgetting Xufeng Cai, Jelena Diakonikolas

COLT 2025 Robustly Learning Monotone Generalized Linear Models via Data Augmentation Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2025 Robustly Learning Monotone Single-Index Models Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2024 Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization Ronak Mehta, Jelena Diakonikolas, Zaid Harchaoui

NeurIPS 2024 Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas, Jelena Diakonikolas

ICML 2024 Robustly Learning Single-Index Models via Alignment Sharpness Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2024 Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2024 Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective Xufeng Cai, Cheuk Yin Lin, Jelena Diakonikolas

ICLR 2024 Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas

ICML 2023 Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization Cheuk Yin Lin, Chaobing Song, Jelena Diakonikolas

NeurIPS 2023 Block-Coordinate Methods and Restarting for Solving Extensive-Form Games Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer

ICML 2023 Cyclic Block Coordinate Descent with Variance Reduction for Composite Nonconvex Optimization Xufeng Cai, Chaobing Song, Stephen Wright, Jelena Diakonikolas

COLT 2023 Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis

NeurIPS 2023 Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis

NeurIPS 2023 Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen Wright

ICML 2023 Robustly Learning a Single Neuron via Sharpness Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2022 A Fast Scale-Invariant Algorithm for Non-Negative Least Squares with Non-Negative Data Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song

NeurIPS 2022 Coordinate Linear Variance Reduction for Generalized Linear Programming Chaobing Song, Cheuk Yin Lin, Stephen Wright, Jelena Diakonikolas

NeurIPS 2022 Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas

AISTATS 2021 Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan

ICML 2021 Parameter-Free Locally Accelerated Conditional Gradients Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta

ICML 2021 Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums Chaobing Song, Stephen J Wright, Jelena Diakonikolas

COLT 2020 Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities Jelena Diakonikolas

AISTATS 2020 Langevin Monte Carlo Without Smoothness Niladri Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter Bartlett

AISTATS 2020 Locally Accelerated Conditional Gradients Jelena Diakonikolas, Alejandro Carderera, Sebastian Pokutta

JMLR 2020 Lower Bounds for Parallel and Randomized Convex Optimization Jelena Diakonikolas, Cristóbal Guzmán

COLT 2019 Lower Bounds for Parallel and Randomized Convex Optimization Jelena Diakonikolas, Cristóbal Guzmán

ICML 2018 Alternating Randomized Block Coordinate Descent Jelena Diakonikolas, Lorenzo Orecchia

ICML 2018 On Acceleration with Noise-Corrupted Gradients Michael Cohen, Jelena Diakonikolas, Lorenzo Orecchia