Rabbat, Mike

8 publications

NeurIPS 2024 The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More Ouail Kitouni, Niklas Nolte, Diane Bouchacourt, Adina Williams, Mike Rabbat, Mark Ibrahim

AISTATS 2022 Federated Learning with Buffered Asynchronous Aggregation John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba

ICML 2022 Federated Learning with Partial Model Personalization Krishna Pillutla, Kshitiz Malik, Abdel-Rahman Mohamed, Mike Rabbat, Maziar Sanjabi, Lin Xiao

UAI 2022 Privacy-Aware Compression for Federated Data Analysis Kamalika Chaudhuri, Chuan Guo, Mike Rabbat

AISTATS 2021 Learning with Gradient Descent and Weakly Convex Losses Dominic Richards, Mike Rabbat

ICML 2020 On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings Mahmoud Assran, Mike Rabbat

ICML 2019 Stochastic Gradient Push for Distributed Deep Learning Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Mike Rabbat

ICML 2019 TarMAC: Targeted Multi-Agent Communication Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Mike Rabbat, Joelle Pineau