ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1606.04838
  4. Cited By
Optimization Methods for Large-Scale Machine Learning
v1v2v3 (latest)

Optimization Methods for Large-Scale Machine Learning

15 June 2016
Léon Bottou
Frank E. Curtis
J. Nocedal
ArXiv (abs)PDFHTML

Papers citing "Optimization Methods for Large-Scale Machine Learning"

50 / 867 papers shown
Title
Analytic natural gradient updates for Cholesky factor in Gaussian
  variational approximation
Analytic natural gradient updates for Cholesky factor in Gaussian variational approximation
Linda S. L. Tan
108
13
0
01 Sep 2021
Adaptive shot allocation for fast convergence in variational quantum
  algorithms
Adaptive shot allocation for fast convergence in variational quantum algorithms
Andi Gu
Angus Lowe
Pavel A. Dub
Patrick J. Coles
A. Arrasmith
67
22
0
23 Aug 2021
Anarchic Federated Learning
Anarchic Federated Learning
Haibo Yang
Xin Zhang
Prashant Khanduri
Jia Liu
FedML
71
59
0
23 Aug 2021
Mobility-Aware Cluster Federated Learning in Hierarchical Wireless
  Networks
Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks
Chenyuan Feng
Heng Yang
Deshun Hu
Zhiwei Zhao
Tony Q.S. Quek
Geyong Min
103
80
0
20 Aug 2021
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and
  Horizontal Data Partitioning
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning
Anirban Das
Timothy Castiglia
Shiqiang Wang
S. Patterson
FedML
104
23
0
19 Aug 2021
A proof of convergence for the gradient descent optimization method with
  random initializations in the training of neural networks with ReLU
  activation for piecewise linear target functions
A proof of convergence for the gradient descent optimization method with random initializations in the training of neural networks with ReLU activation for piecewise linear target functions
Arnulf Jentzen
Adrian Riekert
82
13
0
10 Aug 2021
On the Hyperparameters in Stochastic Gradient Descent with Momentum
On the Hyperparameters in Stochastic Gradient Descent with Momentum
Bin Shi
108
14
0
09 Aug 2021
Coordinate descent on the orthogonal group for recurrent neural network
  training
Coordinate descent on the orthogonal group for recurrent neural network training
E. Massart
V. Abrol
66
11
0
30 Jul 2021
DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient
  Distributed Learning
DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed Learning
Guangfeng Yan
Shao-Lun Huang
Tian-Shing Lan
Linqi Song
MQ
47
7
0
30 Jul 2021
Decentralized Federated Learning: Balancing Communication and Computing
  Costs
Decentralized Federated Learning: Balancing Communication and Computing Costs
Wei Liu
Li Chen
Wenyi Zhang
FedML
71
114
0
26 Jul 2021
A general sample complexity analysis of vanilla policy gradient
A general sample complexity analysis of vanilla policy gradient
Rui Yuan
Robert Mansel Gower
A. Lazaric
138
64
0
23 Jul 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical
  Viewpoints
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints
Shaojie Li
Yong Liu
105
13
0
19 Jul 2021
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and
  Reliability
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability
Qiyiwen Zhang
Zhiqi Bu
Kan Chen
Qi Long
BDLUQCV
72
11
0
18 Jul 2021
Chimera: Efficiently Training Large-Scale Neural Networks with
  Bidirectional Pipelines
Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
Shigang Li
Torsten Hoefler
GNNAI4CELRM
130
138
0
14 Jul 2021
The Bayesian Learning Rule
The Bayesian Learning Rule
Mohammad Emtiyaz Khan
Håvard Rue
BDL
167
83
0
09 Jul 2021
Activated Gradients for Deep Neural Networks
Activated Gradients for Deep Neural Networks
Mei Liu
Liangming Chen
Xiaohao Du
Long Jin
Mingsheng Shang
ODLAI4CE
72
145
0
09 Jul 2021
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity
A. Davtyan
Sepehr Sameni
L. Cerkezi
Givi Meishvili
Adam Bielski
Paolo Favaro
ODL
174
3
0
07 Jul 2021
KAISA: An Adaptive Second-Order Optimizer Framework for Deep Neural
  Networks
KAISA: An Adaptive Second-Order Optimizer Framework for Deep Neural Networks
J. G. Pauloski
Qi Huang
Lei Huang
Shivaram Venkataraman
Kyle Chard
Ian Foster
Zhao-jie Zhang
86
29
0
04 Jul 2021
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth
  Games: Convergence Analysis under Expected Co-coercivity
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity
Nicolas Loizou
Hugo Berard
Gauthier Gidel
Ioannis Mitliagkas
Simon Lacoste-Julien
94
54
0
30 Jun 2021
Never Go Full Batch (in Stochastic Convex Optimization)
Never Go Full Batch (in Stochastic Convex Optimization)
I Zaghloul Amir
Y. Carmon
Tomer Koren
Roi Livni
78
14
0
29 Jun 2021
The Convergence Rate of SGD's Final Iterate: Analysis on Dimension
  Dependence
The Convergence Rate of SGD's Final Iterate: Analysis on Dimension Dependence
Daogao Liu
Zhou Lu
LRM
39
1
0
28 Jun 2021
A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear
  Equality Constrained Optimization with Rank-Deficient Jacobians
A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear Equality Constrained Optimization with Rank-Deficient Jacobians
A. Berahas
Frank E. Curtis
Michael OÑeill
Daniel P. Robinson
76
33
0
24 Jun 2021
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman
  Operators
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators
Zaiwei Chen
S. T. Maguluri
Sanjay Shakkottai
Karthikeyan Shanmugam
OffRL
83
13
0
24 Jun 2021
Memory Augmented Optimizers for Deep Learning
Memory Augmented Optimizers for Deep Learning
Paul-Aymeric McRae
Prasanna Parthasarathi
Mahmoud Assran
Sarath Chandar
ODL
82
3
0
20 Jun 2021
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal
  Sample and Communication Complexities for Federated Learning
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
Prashant Khanduri
Pranay Sharma
Haibo Yang
Min-Fong Hong
Jia Liu
K. Rajawat
P. Varshney
FedML
59
63
0
19 Jun 2021
Interval and fuzzy physics-informed neural networks for uncertain fields
Interval and fuzzy physics-informed neural networks for uncertain fields
J. Fuhg
Ioannis Kalogeris
A. Fau
N. Bouklas
AI4CE
97
19
0
18 Jun 2021
Algorithmic Bias and Data Bias: Understanding the Relation between
  Distributionally Robust Optimization and Data Curation
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation
Agnieszka Słowik
Léon Bottou
FaML
77
19
0
17 Jun 2021
A Survey on Fault-tolerance in Distributed Optimization and Machine
  Learning
A Survey on Fault-tolerance in Distributed Optimization and Machine Learning
Shuo Liu
AI4CEOOD
79
13
0
16 Jun 2021
On the Sample Complexity and Metastability of Heavy-tailed Policy Search
  in Continuous Control
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control
Amrit Singh Bedi
Anjaly Parayil
Junyu Zhang
Mengdi Wang
Alec Koppel
90
15
0
15 Jun 2021
Federated Learning with Buffered Asynchronous Aggregation
Federated Learning with Buffered Asynchronous Aggregation
John Nguyen
Kshitiz Malik
Hongyuan Zhan
Ashkan Yousefpour
Michael G. Rabbat
Mani Malek
Dzmitry Huba
FedML
99
313
0
11 Jun 2021
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm
  via Langevin Monte Carlo within Gibbs
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs
Vincent Plassier
Maxime Vono
Alain Durmus
Eric Moulines
78
17
0
11 Jun 2021
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max
  Optimization Problems
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max Optimization Problems
Babak Barazandeh
Tianjian Huang
George Michailidis
86
12
0
10 Jun 2021
A Continuized View on Nesterov Acceleration for Stochastic Gradient
  Descent and Randomized Gossip
A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip
Mathieu Even
Raphael Berthier
Francis R. Bach
Nicolas Flammarion
Pierre Gaillard
Aymeric Dieuleveut
Laurent Massoulié
Adrien B. Taylor
124
20
0
10 Jun 2021
The dilemma of quantum neural networks
The dilemma of quantum neural networks
Yan Qian
Xinbiao Wang
Yuxuan Du
Xingyao Wu
Dacheng Tao
59
31
0
09 Jun 2021
Asynchronous Distributed Optimization with Redundancy in Cost Functions
Asynchronous Distributed Optimization with Redundancy in Cost Functions
Shuo Liu
Nirupam Gupta
Nitin H. Vaidya
62
3
0
07 Jun 2021
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models
Courtney Paquette
Elliot Paquette
ODL
102
14
0
07 Jun 2021
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural
  Networks
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks
Chaoyang He
Emir Ceyani
Keshav Balasubramanian
M. Annavaram
Salman Avestimehr
FedML
73
52
0
04 Jun 2021
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and
  Interpolation Learning
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning
Blake E. Woodworth
Nathan Srebro
81
22
0
04 Jun 2021
Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Valerii Likhosherstov
Xingyou Song
K. Choromanski
Jared Davis
Adrian Weller
AI4CE
79
5
0
04 Jun 2021
Local Adaptivity in Federated Learning: Convergence and Consistency
Local Adaptivity in Federated Learning: Convergence and Consistency
Jianyu Wang
Zheng Xu
Zachary Garrett
Zachary B. Charles
Luyang Liu
Gauri Joshi
FedML
99
40
0
04 Jun 2021
Improving Neural Network Robustness via Persistency of Excitation
Improving Neural Network Robustness via Persistency of Excitation
Kaustubh Sridhar
O. Sokolsky
Insup Lee
James Weimer
AAML
97
20
0
03 Jun 2021
Fine-grained Generalization Analysis of Structured Output Prediction
Fine-grained Generalization Analysis of Structured Output Prediction
Waleed Mustafa
Yunwen Lei
Antoine Ledent
Marius Kloft
80
9
0
31 May 2021
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective
Kushal Chakrabarti
Nikhil Chopra
ODLAI4CE
83
9
0
31 May 2021
Energy-Efficient and Federated Meta-Learning via Projected Stochastic
  Gradient Ascent
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent
Anis Elgabli
Chaouki Ben Issaid
Amrit Singh Bedi
M. Bennis
Vaneet Aggarwal
FedML
37
4
0
31 May 2021
Detecting Backdoor in Deep Neural Networks via Intentional Adversarial
  Perturbations
Detecting Backdoor in Deep Neural Networks via Intentional Adversarial Perturbations
Mingfu Xue
Yinghao Wu
Zhiyu Wu
Yushu Zhang
Jian Wang
Weiqiang Liu
AAML
54
12
0
29 May 2021
A Stochastic Alternating Balance $k$-Means Algorithm for Fair Clustering
A Stochastic Alternating Balance kkk-Means Algorithm for Fair Clustering
Suyun Liu
Luis Nunes Vicente
98
11
0
29 May 2021
Online Statistical Inference for Parameters Estimation with
  Linear-Equality Constraints
Online Statistical Inference for Parameters Estimation with Linear-Equality Constraints
Ruiqi Liu
Mingao Yuan
Zuofeng Shang
63
6
0
21 May 2021
Clustered Sampling: Low-Variance and Improved Representativity for
  Clients Selection in Federated Learning
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni
Richard Vidal
Laetitia Kameni
Marco Lorenzi
FedML
77
196
0
12 May 2021
A Twin Neural Model for Uplift
A Twin Neural Model for Uplift
Mouloud Belbahri
Olivier Gandouet
A. Murua
V. Nia
CML
13
1
0
11 May 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features
A Geometric Analysis of Neural Collapse with Unconstrained Features
Zhihui Zhu
Tianyu Ding
Jinxin Zhou
Xiao Li
Chong You
Jeremias Sulam
Qing Qu
88
204
0
06 May 2021
Previous
123...678...161718
Next