Publications

Mixed Nash for Robust Federated Learning
Wanyun Xie, Thomas Pethick, Ali Ramezani-Kebrya, Volkan Cevher
Transactions on Machine Learning Research (TMLR) 2024
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Stable nonconvex-nonconcave training via linear interpolation
Thomas Pethick, Wanyun Xie, Volkan Cevher
Neural Information Processing Systems (NeurIPS) 2023 (spotlight)
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Solving stochastic weak Minty variational inequalities without increasing batch size
Thomas Pethick, Olivier Fercoq, Puya Latafat, Panagiotis Patrinos and Volkan Cevher
International Conference on Learning Representations (ICLR) 2023
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Federated Learning under Covariate Shifts with Generalization Guarantees
Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher
Transactions on Machine Learning Research (TMLR) 2023
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Finding actual descent directions for adversarial training
Fabian Latorre, Igor Krawczuk, Leello Tadesse Dadi, Thomas Pethick and Volkan Cevher
International Conference on Learning Representations (ICLR) 2023
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Revisiting adversarial training for the worst-performing class
Thomas Pethick and Grigorios Chrysos and Volkan Cevher
Transactions on Machine Learning Research (TMLR) 2022
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Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems
Thomas Pethick, Puya Latafat, Panagiotis Patrinos, Olivier Fercoq, Volkan Cevher
The International Conference on Learning Representations (ICLR) 2022 (spotlight)
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Sifting through the noise: Universal first-order methods for stochastic variational inequalities
Kimon Antonakopoulos, Thomas Pethick, Ali Kavis, Panayotis Mertikopoulos, Volkan Cevher
Neural Information Processing Systems (NeurIPS) 2021
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Subquadratic Overparameterization for Shallow Neural Networks
Chaehwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher
Neural Information Processing Systems (NeurIPS) 2021
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