Safe Adaptive Importance Sampling

7 November 2017

Papers citing "Safe Adaptive Importance Sampling"

6 / 6 papers shown

Title
Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models Ethan Pickering T. Sapsis 16 6 0 27 Aug 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning Lung-Chuang Wang Yongxin Guo Tao R. Lin Xiaoying Tang FedML 16 20 0 27 May 2022
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback Boxin Zhao Lingxiao Wang Mladen Kolar Ziqi Liu Zhiqiang Zhang Jun Zhou Chaochao Chen FedML 26 9 0 28 Dec 2021
Adaptive Importance Sampling meets Mirror Descent: a Bias-variance tradeoff Anna Korba Franccois Portier 14 12 0 29 Oct 2021
Optimal Importance Sampling for Federated Learning Elsa Rizk Stefan Vlaski A. H. Sayed FedML 27 45 0 26 Oct 2020
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 113 259 0 10 Dec 2012