2025
Efficient Spectral-Spatial Fusion With Multiscale and Adaptive Attention for Hyperspectral Image Classification.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025
2024
Faster Rates for Compressed Federated Learning with Client-Variance Reduction.
SIAM J. Math. Data Sci., March, 2024
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2022
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization.
SIAM J. Math. Data Sci., 2022
Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization.
J. Mach. Learn. Res., 2022
Optimal in-place suffix sorting.
Inf. Comput., 2022
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation.
Proceedings of the International Conference on Machine Learning, 2022
2021
EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback.
CoRR, 2021
FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning.
CoRR, 2021
A Short Note of PAGE: Optimal Convergence Rates for Nonconvex Optimization.
CoRR, 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method.
CoRR, 2021
ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation.
CoRR, 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021
MARINA: Faster Non-Convex Distributed Learning with Compression.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization.
CoRR, 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference.
Mach. Learn., 2019
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
A unified variance-reduced accelerated gradient method for convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Gradient Boosting with Piece-Wise Linear Regression Trees.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Learning Two-layer Neural Networks with Symmetric Inputs.
Proceedings of the 7th International Conference on Learning Representations, 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization.
Proceedings of the Conference on Learning Theory, 2019
2018
A Fast Polynomial-time Primal-Dual Projection Algorithm for Linear Programming.
CoRR, 2018
An Anderson-Chebyshev Mixing Method for Nonlinear Optimization.
CoRR, 2018
Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference.
CoRR, 2018
A Two-Stage Mechanism for Ordinal Peer Assessment.
Proceedings of the Algorithmic Game Theory - 11th International Symposium, 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
Modeling and Routing for Predictable Dynamic Networks.
CoRR, 2017
2015
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015