Zhize Li
According to our database1,
Zhize Li
authored at least 33 papers
between 2015 and 2023.
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Bibliography
2023
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression.
CoRR, 2023
2022
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization.
SIAM J. Math. Data Sci., 2022
J. Mach. Learn. Res., 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
CoRR, 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
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
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
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
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the Conference on Learning Theory, 2019
2018
CoRR, 2018
Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference.
CoRR, 2018
Proceedings of the Algorithmic Game Theory - 11th International Symposium, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015