Faster convergence rates of relaxed Peaceman-Rachford and ADMM under regularity assumptions

von Davis, Damek
Veröffentlicht in Mathematics of operations research (2017)

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection

von Cai, HanQin
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 21 of 36 (2022)

Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems

von Chen, Tianyi
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 30 of 36 (2022)

AN IMPROVED ANALYSIS OF STOCHASTIC GRADIENT DESCENT WITH MOMENTUM

von Liu, Yanli
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 22 of 27 (2021)

Compressive sensing for wireless networks

von Han, Zhu
Veröffentlicht 2013

Splitting methods in communication, imaging, science, and engineering

Veröffentlicht 2016

A ZEROTH-ORDER BLOCK COORDINATE DESCENT ALGORITHM FOR HUGE-SCALE BLACK-BOX OPTIMIZATION

von CAI, HANQIN
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 2 of 16 (2022)

PROVABLY CORRECT OPTIMIZATION AND EXPLORATION WITH NON-LINEAR POLICIES

von FENG, FEI
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 5 of 16 (2022)

Hyperparameter Tuning is All You Need for LISTA

von Chen, Xiaohan
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 14 of 36 (2022)

AN IMPROVED ANALYSIS OF (VARIANCE-REDUCED) POLICY GRADIENT AND NATURAL POLICY GRADIENT METHODS

von Liu, Yanli
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 10 of 27 (2021)

An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders

von Huang, Xinmeng
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 5 of 36 (2022)

Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression

von Huang, Xinmeng
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 25 of 50 (2023)

PROVABLY EFFICIENT EXPLORATION FOR REINFORCEMENT LEARNING USING UNSUPERVISED LEARNING

von Feng, Fei
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 27 of 27 (2021)

Exponential Graph is Provably Efficient for Decentralized Deep Training

von Ying, Bicheng
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 17 of 36 (2022)

ACCELERATING GOSSIP SGD WITH PERIODIC GLOBAL AVERAGING

von CHEN, YIMING
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 3 of 16 (2022)

Communication-Efficient Topologies for Decentralized Learning with O(1) Consensus Rate

von Song, Zhuoqing
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 2 of 50 (2023)

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting

von Zhou, Tian
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 17 of 50 (2023)