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Coordinate Descent with Bandit Sampling
v1v2 (latest)

Coordinate Descent with Bandit Sampling

8 December 2017
Farnood Salehi
Patrick Thiran
L. E. Celis
ArXiv (abs)PDFHTML

Papers citing "Coordinate Descent with Bandit Sampling"

13 / 13 papers shown
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Sijia Zhou
Yunwen Lei
Ata Kabán
355
0
0
03 Apr 2025
REWAFL: Residual Energy and Wireless Aware Participant Selection for
  Efficient Federated Learning over Mobile Devices
REWAFL: Residual Energy and Wireless Aware Participant Selection for Efficient Federated Learning over Mobile DevicesIEEE Transactions on Mobile Computing (IEEE TMC), 2023
Y. Li
X. Qin
J. Geng
Ruoxin Chen
Y. Hou
Yonghai Gong
M. Pan
Peng Zhang
179
4
0
24 Sep 2023
Adaptive Sketches for Robust Regression with Importance Sampling
Adaptive Sketches for Robust Regression with Importance SamplingInternational Workshop and International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM), 2022
S. Mahabadi
David P. Woodruff
Samson Zhou
151
6
0
16 Jul 2022
Transformer with Memory Replay
Transformer with Memory ReplayAAAI Conference on Artificial Intelligence (AAAI), 2022
R. Liu
Barzan Mozafari
OffRL
317
5
0
19 May 2022
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Boxin Zhao
Lingxiao Wang
Mladen Kolar
Ziqi Liu
Qing Cui
Jun Zhou
Chaochao Chen
FedML
660
12
0
28 Dec 2021
Adam with Bandit Sampling for Deep Learning
Adam with Bandit Sampling for Deep LearningNeural Information Processing Systems (NeurIPS), 2020
Rui Liu
Tianyi Wu
Barzan Mozafari
206
28
0
24 Oct 2020
Client Selection in Federated Learning: Convergence Analysis and
  Power-of-Choice Selection Strategies
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
Yae Jee Cho
Jianyu Wang
Gauri Joshi
FedML
340
494
0
03 Oct 2020
Minimal Variance Sampling with Provable Guarantees for Fast Training of
  Graph Neural Networks
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural NetworksKnowledge Discovery and Data Mining (KDD), 2020
Weilin Cong
R. Forsati
M. Kandemir
M. Mahdavi
307
95
0
24 Jun 2020
Stochastic Coordinate Minimization with Progressive Precision for
  Stochastic Convex Optimization
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex OptimizationInternational Conference on Machine Learning (ICML), 2020
Sudeep Salgia
Qing Zhao
Sattar Vakili
187
2
0
11 Mar 2020
Faster Activity and Data Detection in Massive Random Access: A
  Multi-armed Bandit Approach
Faster Activity and Data Detection in Massive Random Access: A Multi-armed Bandit ApproachIEEE Internet of Things Journal (IEEE IoT J.), 2020
Jialin Dong
Jun Zhang
Yuanming Shi
Jessie Hui Wang
136
26
0
28 Jan 2020
Online Variance Reduction with Mixtures
Online Variance Reduction with Mixtures
Zalan Borsos
Sebastian Curi
Kfir Y. Levy
Andreas Krause
150
15
0
29 Mar 2019
Distributed Learning with Sparse Communications by Identification
Distributed Learning with Sparse Communications by Identification
Dmitry Grishchenko
F. Iutzeler
J. Malick
Massih-Reza Amini
163
19
0
10 Dec 2018
Online Variance Reduction for Stochastic Optimization
Online Variance Reduction for Stochastic Optimization
Zalan Borsos
Andreas Krause
Kfir Y. Levy
230
25
0
13 Feb 2018
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