Ramezani-Kebrya, Ali

11 publications

ICLR 2025 Addressing Label Shift in Distributed Learning via Entropy Regularization Zhiyuan Wu, Changkyu Choi, Xiangcheng Cao, Volkan Cevher, Ali Ramezani-Kebrya

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

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

TMLR 2024 Mixed Nash for Robust Federated Learning Wanyun Xie, Thomas Pethick, Ali Ramezani-Kebrya, Volkan Cevher

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

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

TMLR 2023 Federated Learning Under Covariate Shifts with Generalization Guarantees Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher

TMLR 2022 MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks Ali Ramezani-Kebrya, Iman Tabrizian, Fartash Faghri, Petar Popovski

JMLR 2021 NUQSGD: Provably Communication-Efficient Data-Parallel SGD via Nonuniform Quantization Ali Ramezani-Kebrya, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan Alistarh, Daniel M. Roy

NeurIPS 2021 Subquadratic Overparameterization for Shallow Neural Networks ChaeHwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher

NeurIPS 2020 Adaptive Gradient Quantization for Data-Parallel SGD Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel M. Roy, Ali Ramezani-Kebrya