Jelena Diakonikolas

88 papers A* 25A 4Misc 1Journal 56Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Delayed-Update Cyclic Algorithm for Variational Inequalities. CoRR Yi Wei, Xufeng Cai, Jelena Diakonikolas
2026	J	`jnl`	Near-Linear Runtime for a Classical Matrix Preconditioning Algorithm. J. ACM Xufeng Cai, Jason M. Altschuler, Jelena Diakonikolas
2026	J	`jnl`	Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective. SIAM J. Optim. Jelena Diakonikolas, Cristóbal Guzmán
2026	J	`jnl`	Robust Learning of a Group DRO Neuron. CoRR Guyang Cao, Shuyao Li, Sushrut Karmalkar, Jelena Diakonikolas
2025	J	`jnl`	Distributionally Robust Optimization with Adversarial Data Contamination. CoRR Shuyao Li, Ilias Diakonikolas, Jelena Diakonikolas
2025	A*	`conf`	Last Iterate Convergence of Incremental Methods as a Model of Forgetting. ICLR Xufeng Cai, Jelena Diakonikolas
2025	J	`jnl`	Linear Regression under Missing or Corrupted Coordinates. CoRR Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas
2025	J	`jnl`	Near-Linear Runtime for a Classical Matrix Preconditioning Algorithm. CoRR Xufeng Cai, Jason M. Altschuler, Jelena Diakonikolas
2025	A*	`conf`	Robustly Learning Monotone Generalized Linear Models via Data Augmentation. COLT Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2025	J	`jnl`	Robustly Learning Monotone Generalized Linear Models via Data Augmentation. CoRR Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2025	J	`jnl`	Robustly Learning Monotone Single-Index Models. CoRR Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	A Primal-Dual Algorithm for Faster Distributionally Robust Optimization. CoRR Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui
2024	J	`jnl`	Complementary composite minimization, small gradients in general norms, and applications. Math. Program. Jelena Diakonikolas, Cristóbal Guzmán
2024	A*	`conf`	Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization. NeurIPS Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui
2024	J	`jnl`	Last Iterate Convergence of Incremental Methods and Applications in Continual Learning. CoRR Xufeng Cai, Jelena Diakonikolas
2024	A*	`conf`	Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise. NeurIPS Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise. CoRR Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective. CoRR Jelena Diakonikolas, Cristóbal Guzmán
2024	J	`jnl`	Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. CoRR Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
2024	A*	`conf`	Robustly Learning Single-Index Models via Alignment Sharpness. ICML Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Robustly Learning Single-Index Models via Alignment Sharpness. CoRR Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2024	A*	`conf`	Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models. NeurIPS Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models. CoRR Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2024	A*	`conf`	Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective. NeurIPS Xufeng Cai, Cheuk Yin Lin, Jelena Diakonikolas
2024	A*	`conf`	Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions. ICLR Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
2023	A*	`conf`	Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization. ICML Cheuk Yin Lin, Chaobing Song, Jelena Diakonikolas
2023	J	`jnl`	Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization. CoRR Cheuk Yin Lin, Chaobing Song, Jelena Diakonikolas
2023	A*	`conf`	Block-Coordinate Methods and Restarting for Solving Extensive-Form Games. NeurIPS Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer
2023	J	`jnl`	Block-Coordinate Methods and Restarting for Solving Extensive-Form Games. CoRR Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer
2023	A*	`conf`	Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization. ICML Xufeng Cai, Chaobing Song, Stephen J. Wright, Jelena Diakonikolas
2023	J	`jnl`	Cyclic Coordinate Dual Averaging with Extrapolation. SIAM J. Optim. Chaobing Song, Jelena Diakonikolas
2023	J	`jnl`	Empirical Risk Minimization with Shuffled SGD: A Primal-Dual Perspective and Improved Bounds. CoRR Xufeng Cai, Cheuk Yin Lin, Jelena Diakonikolas
2023	A*	`conf`	Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. COLT Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
2023	J	`jnl`	Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. CoRR Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
2023	A*	`conf`	Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. NeurIPS Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis
2023	J	`jnl`	Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. CoRR Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
2023	A*	`conf`	Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. NeurIPS Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
2023	A*	`conf`	Robustly Learning a Single Neuron via Sharpness. ICML Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2023	J	`jnl`	Robustly Learning a Single Neuron via Sharpness. CoRR Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2023	J	`jnl`	Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions. CoRR Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
2022	A*	`conf`	A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data. NeurIPS Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song
2022	J	`jnl`	A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data. CoRR Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song
2022	J	`jnl`	A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems. CoRR Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas
2022	A*	`conf`	Coordinate Linear Variance Reduction for Generalized Linear Programming. NeurIPS Chaobing Song, Cheuk Yin Lin, Stephen J. Wright, Jelena Diakonikolas
2022	J	`jnl`	Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization. CoRR Xufeng Cai, Chaobing Song, Stephen J. Wright, Jelena Diakonikolas
2022	J	`jnl`	Potential Function-Based Framework for Minimizing Gradients in Convex and Min-Max Optimization. SIAM J. Optim. Jelena Diakonikolas, Puqian Wang
2022	A*	`conf`	Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions. NeurIPS Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas
2021	J	`jnl`	Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems. CoRR Jelena Diakonikolas, Cristóbal Guzmán
2021	J	`jnl`	Coordinate Linear Variance Reduction for Generalized Linear Programming. CoRR Chaobing Song, Cheuk Yin Lin, Stephen J. Wright, Jelena Diakonikolas
2021	A	`conf`	Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization. AISTATS Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan
2021	J	`jnl`	Fast Cyclic Coordinate Dual Averaging with Extrapolation for Generalized Variational Inequalities. CoRR Chaobing Song, Jelena Diakonikolas
2021	J	`jnl`	Generalized Momentum-Based Methods: A Hamiltonian Perspective. SIAM J. Optim. Jelena Diakonikolas, Michael I. Jordan
2021	A*	`conf`	Parameter-free Locally Accelerated Conditional Gradients. ICML Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
2021	J	`jnl`	Parameter-free Locally Accelerated Conditional Gradients. CoRR Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
2021	J	`jnl`	Potential Function-based Framework for Making the Gradients Small in Convex and Min-Max Optimization. CoRR Jelena Diakonikolas, Puqian Wang
2021	A*	`conf`	Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums. ICML Chaobing Song, Stephen J. Wright, Jelena Diakonikolas
2021	J	`jnl`	Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums. CoRR Chaobing Song, Stephen J. Wright, Jelena Diakonikolas
2020	J	`jnl`	Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization. CoRR Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan
2020	J	`jnl`	Fair Packing and Covering on a Relative Scale. SIAM J. Optim. Jelena Diakonikolas, Maryam Fazel, Lorenzo Orecchia
2020	A*	`conf`	Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities. COLT Jelena Diakonikolas
2020	J	`jnl`	Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities. CoRR Jelena Diakonikolas
2020	J	`jnl`	Hybrid Scheduling in Heterogeneous Half- and Full-Duplex Wireless Networks. IEEE/ACM Trans. Netw. Tingjun Chen, Jelena Diakonikolas, Javad Ghaderi, Gil Zussman
2020	A	`conf`	Langevin Monte Carlo without smoothness. AISTATS Niladri S. Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter L. Bartlett
2020	A	`conf`	Locally Accelerated Conditional Gradients. AISTATS Jelena Diakonikolas, Alejandro Carderera, Sebastian Pokutta
2020	J	`jnl`	Lower Bounds for Parallel and Randomized Convex Optimization. J. Mach. Learn. Res. Jelena Diakonikolas, Cristóbal Guzmán
2019	—	`conf`	A Hierarchical WDM-Based Scalable Data Center Network Architecture. ICC Maotong Xu, Jelena Diakonikolas, Eytan H. Modiano, Suresh Subramaniam
2019	J	`jnl`	A Hierarchical WDM-based Scalable Data Center Network Architecture. CoRR Maotong Xu, Jelena Diakonikolas, Eytan H. Modiano, Suresh Subramaniam
2019	J	`jnl`	Conjugate Gradients and Accelerated Methods Unified: The Approximate Duality Gap View. CoRR Jelena Diakonikolas, Lorenzo Orecchia
2019	J	`jnl`	Generalized Momentum-Based Methods: A Hamiltonian Perspective. CoRR Jelena Diakonikolas, Michael I. Jordan
2019	J	`jnl`	Langevin Monte Carlo without Smoothness. CoRR Niladri S. Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter L. Bartlett
2019	J	`jnl`	Locally Accelerated Conditional Gradients. CoRR Alejandro Carderera, Jelena Diakonikolas, Sebastian Pokutta
2019	A*	`conf`	Lower Bounds for Parallel and Randomized Convex Optimization. COLT Jelena Diakonikolas, Cristóbal Guzmán
2019	J	`jnl`	The Approximate Duality Gap Technique: A Unified Theory of First-Order Methods. SIAM J. Optim. Jelena Diakonikolas, Lorenzo Orecchia
2018	A	`conf`	Accelerated Extra-Gradient Descent: A Novel Accelerated First-Order Method. ITCS Jelena Diakonikolas, Lorenzo Orecchia
2018	A*	`conf`	Alternating Randomized Block Coordinate Descent. ICML Jelena Diakonikolas, Lorenzo Orecchia
2018	Misc	`conf`	Fairness and Delay in Heterogeneous Half- and Full-Duplex Wireless Networks. ACSSC Tingjun Chen, Jelena Diakonikolas, Javad Ghaderi, Gil Zussman
2018	J	`jnl`	Hybrid Scheduling in Heterogeneous Half- and Full-Duplex Wireless Networks. CoRR Tingjun Chen, Jelena Diakonikolas, Javad Ghaderi, Gil Zussman
2018	A*	`conf`	Hybrid Scheduling in Heterogeneous Half-and Full-Duplex Wireless Networks. INFOCOM Tingjun Chen, Jelena Diakonikolas, Javad Ghaderi, Gil Zussman
2018	J	`jnl`	Lower Bounds for Parallel and Randomized Convex Optimization. CoRR Jelena Diakonikolas, Cristóbal Guzmán
2018	A*	`conf`	On Acceleration with Noise-Corrupted Gradients. ICML Michael Cohen, Jelena Diakonikolas, Lorenzo Orecchia
2018	J	`jnl`	On Acceleration with Noise-Corrupted Gradients. CoRR Michael B. Cohen, Jelena Diakonikolas, Lorenzo Orecchia
2018	J	`jnl`	On the Rate Regions of Single-Channel and Multi-Channel Full-Duplex Links. IEEE/ACM Trans. Netw. Jelena Diakonikolas, Gil Zussman
2018	J	`jnl`	Width-Independence Beyond Linear Objectives: Distributed Fair Packing and Covering Algorithms. CoRR Jelena Diakonikolas, Maryam Fazel, Lorenzo Orecchia
2017	J	`jnl`	Accelerated Extra-Gradient Descent: A Novel Accelerated First-Order Method. CoRR Jelena Diakonikolas, Lorenzo Orecchia
2017	—	`conf`	Demo abstract: Full-duplex with a compact frequency domain equalization-based RF canceller. INFOCOM Workshops Tingjun Chen, Jin Zhou, Mahmood Baraani Dastjerdi, Jelena Diakonikolas, Harish Krishnaswamy, Gil Zussman
2017	J	`jnl`	Integrated Full Duplex Radios. IEEE Commun. Mag. Jin Zhou, Negar Reiskarimian, Jelena Diakonikolas, Tolga Dinc, Tingjun Chen, Gil Zussman, Harish Krishnaswamy
2017	J	`jnl`	Solving Packing and Covering LPs in Õ(1/ε CoRR Jelena Diakonikolas, Lorenzo Orecchia
2017	J	`jnl`	The Approximate Duality Gap Technique: A Unified Theory of First-Order Methods. CoRR Jelena Diakonikolas, Lorenzo Orecchia