Efficient Optimization Algorithms for Nonconvex Machine Learning Problems.
PhD thesis, 2024
Delving into the Convergence of Generalized Smooth Minimax Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Finding Local Minima Efficiently in Decentralized Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Distributed Dynamic Safe Screening Algorithms for Sparse Regularization.
CoRR, 2022
Doubly Sparse Asynchronous Learning for Stochastic Composite Optimization.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Communication-Efficient Adam-Type Algorithms for Distributed Data Mining.
Proceedings of the IEEE International Conference on Data Mining, 2022
A Faster Decentralized Algorithm for Nonconvex Minimax Problems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Learning Better Visual Data Similarities via New Grouplet Non-Euclidean Embedding.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
A Unified q-Memorization Framework for Asynchronous Stochastic Optimization.
J. Mach. Learn. Res., 2020
Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019