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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 / 1,491 papers shown
Stochastic Runge-Kutta methods and adaptive SGD-G2 stochastic gradient
  descent
Stochastic Runge-Kutta methods and adaptive SGD-G2 stochastic gradient descentInternational Conference on Pattern Recognition (ICPR), 2020
I. Ayadi
Gabriel Turinici
ODL
113
9
0
20 Feb 2020
Adaptive Sampling Distributed Stochastic Variance Reduced Gradient for
  Heterogeneous Distributed Datasets
Adaptive Sampling Distributed Stochastic Variance Reduced Gradient for Heterogeneous Distributed Datasets
Ilqar Ramazanli
Han Nguyen
Hai Pham
Sashank J. Reddi
Barnabás Póczós
256
11
0
20 Feb 2020
A Unified Convergence Analysis for Shuffling-Type Gradient Methods
A Unified Convergence Analysis for Shuffling-Type Gradient MethodsJournal of machine learning research (JMLR), 2020
Lam M. Nguyen
Quoc Tran-Dinh
Dzung Phan
Phuong Ha Nguyen
Marten van Dijk
304
91
0
19 Feb 2020
Multiresolution Tensor Learning for Efficient and Interpretable Spatial
  Analysis
Multiresolution Tensor Learning for Efficient and Interpretable Spatial AnalysisInternational Conference on Machine Learning (ICML), 2020
Jung Yeon Park
K. T. Carr
Stephan Zhang
Yisong Yue
Rose Yu
344
14
0
13 Feb 2020
Stochastic Approximate Gradient Descent via the Langevin Algorithm
Stochastic Approximate Gradient Descent via the Langevin AlgorithmAAAI Conference on Artificial Intelligence (AAAI), 2020
Yixuan Qiu
Tianlin Li
171
5
0
13 Feb 2020
Gradient tracking and variance reduction for decentralized optimization
  and machine learning
Gradient tracking and variance reduction for decentralized optimization and machine learning
Ran Xin
S. Kar
U. Khan
170
10
0
13 Feb 2020
RFN: A Random-Feature Based Newton Method for Empirical Risk
  Minimization in Reproducing Kernel Hilbert Spaces
RFN: A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert SpacesIEEE Transactions on Signal Processing (TSP), 2020
Ting-Jui Chang
Shahin Shahrampour
323
3
0
12 Feb 2020
On the distance between two neural networks and the stability of
  learning
On the distance between two neural networks and the stability of learningNeural Information Processing Systems (NeurIPS), 2020
Jeremy Bernstein
Arash Vahdat
Yisong Yue
Xuan Li
ODL
507
70
0
09 Feb 2020
Better Theory for SGD in the Nonconvex World
Better Theory for SGD in the Nonconvex World
Ahmed Khaled
Peter Richtárik
423
216
0
09 Feb 2020
Low Rank Saddle Free Newton: A Scalable Method for Stochastic Nonconvex
  Optimization
Low Rank Saddle Free Newton: A Scalable Method for Stochastic Nonconvex Optimization
Thomas O'Leary-Roseberry
Nick Alger
Omar Ghattas
ODL
192
9
0
07 Feb 2020
Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter -- a
  Case Study
Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter -- a Case StudyIFAC-PapersOnLine (IFAC-PapersOnLine), 2020
M. Hotvedt
B. Grimstad
Lars Imsland
135
24
0
07 Feb 2020
Differentially Quantized Gradient Methods
Differentially Quantized Gradient MethodsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Chung-Yi Lin
V. Kostina
B. Hassibi
MQ
341
8
0
06 Feb 2020
Almost Sure Convergence of Dropout Algorithms for Neural Networks
Almost Sure Convergence of Dropout Algorithms for Neural Networks
Albert Senen-Cerda
J. Sanders
244
11
0
06 Feb 2020
Faster On-Device Training Using New Federated Momentum Algorithm
Faster On-Device Training Using New Federated Momentum Algorithm
Zhouyuan Huo
Qian Yang
Bin Gu
Heng-Chiao Huang
FedML
335
54
0
06 Feb 2020
Large Batch Training Does Not Need Warmup
Large Batch Training Does Not Need Warmup
Zhouyuan Huo
Bin Gu
Heng-Chiao Huang
AI4CEODL
157
5
0
04 Feb 2020
Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex
  Envelopes
Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes
Zaiwei Chen
S. T. Maguluri
Sanjay Shakkottai
Karthikeyan Shanmugam
256
34
0
03 Feb 2020
Replica Exchange for Non-Convex Optimization
Replica Exchange for Non-Convex OptimizationJournal of machine learning research (JMLR), 2020
Jing-rong Dong
Xin T. Tong
411
22
0
23 Jan 2020
Intermittent Pulling with Local Compensation for Communication-Efficient
  Federated Learning
Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
Yining Qi
Zhihao Qu
Song Guo
Xin Gao
Ruixuan Li
Baoliu Ye
FedML
157
9
0
22 Jan 2020
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor
  Analysis
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis
Christopher J. Urban
Daniel J. Bauer
BDL
385
37
0
22 Jan 2020
Stochastic Item Descent Method for Large Scale Equal Circle Packing
  Problem
Stochastic Item Descent Method for Large Scale Equal Circle Packing Problem
Kun He
Min Zhang
Jianrong Zhou
Yan Jin
ChuMin Li
61
2
0
22 Jan 2020
Adaptive Stochastic Optimization
Adaptive Stochastic OptimizationIEEE Signal Processing Magazine (IEEE Signal Process. Mag.), 2020
Frank E. Curtis
K. Scheinberg
ODL
154
32
0
18 Jan 2020
Learning the Ising Model with Generative Neural Networks
Learning the Ising Model with Generative Neural NetworksPhysical Review Research (PRResearch), 2020
Francesco DÁngelo
Lucas Böttcher
AI4CE
125
32
0
15 Jan 2020
Secure multiparty computations in floating-point arithmetic
Secure multiparty computations in floating-point arithmeticInformation and Inference A Journal of the IMA (JIII), 2020
Chuan Guo
Awni Y. Hannun
Brian Knott
Laurens van der Maaten
M. Tygert
Ruiyu Zhu
FedML
138
18
0
09 Jan 2020
Distributionally Robust Deep Learning using Hardness Weighted Sampling
Distributionally Robust Deep Learning using Hardness Weighted SamplingMachine Learning for Biomedical Imaging (MLBI), 2020
Lucas Fidon
Michael Aertsen
Thomas Deprest
Doaa Emam
Frédéric Guffens
...
Andrew Melbourne
Sébastien Ourselin
Jan Deprest
Georg Langs
Tom Vercauteren
OOD
340
10
0
08 Jan 2020
Stochastic gradient-free descents
Stochastic gradient-free descents
Xiaopeng Luo
Xin Xu
ODL
220
3
0
31 Dec 2019
Characterizing the Decision Boundary of Deep Neural Networks
Characterizing the Decision Boundary of Deep Neural Networks
Hamid Karimi
Hanyu Wang
Shucheng Zhou
276
80
0
24 Dec 2019
Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale
  Stochastic Approximation
Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale Stochastic ApproximationSIAM Journal of Control and Optimization (SICON), 2019
Thinh T. Doan
251
37
0
23 Dec 2019
Second-order Information in First-order Optimization Methods
Second-order Information in First-order Optimization Methods
Yuzheng Hu
Licong Lin
Shange Tang
ODL
162
2
0
20 Dec 2019
Learning Convex Optimization Control Policies
Learning Convex Optimization Control PoliciesConference on Learning for Dynamics & Control (L4DC), 2019
Akshay Agrawal
Shane T. Barratt
Stephen P. Boyd
Bartolomeo Stellato
153
80
0
19 Dec 2019
Randomized Reactive Redundancy for Byzantine Fault-Tolerance in
  Parallelized Learning
Randomized Reactive Redundancy for Byzantine Fault-Tolerance in Parallelized Learning
Nirupam Gupta
Nitin H. Vaidya
FedML
190
8
0
19 Dec 2019
Optimization for deep learning: theory and algorithms
Optimization for deep learning: theory and algorithms
Tian Ding
ODL
346
179
0
19 Dec 2019
PyHessian: Neural Networks Through the Lens of the Hessian
PyHessian: Neural Networks Through the Lens of the Hessian
Z. Yao
A. Gholami
Kurt Keutzer
Michael W. Mahoney
ODL
370
346
0
16 Dec 2019
A Machine Learning Framework for Solving High-Dimensional Mean Field
  Game and Mean Field Control Problems
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control ProblemsProceedings of the National Academy of Sciences of the United States of America (PNAS), 2019
Lars Ruthotto
Stanley Osher
Wuchen Li
L. Nurbekyan
Samy Wu Fung
AI4CE
363
257
0
04 Dec 2019
Federated Learning with Personalization Layers
Federated Learning with Personalization Layers
Manoj Ghuhan Arivazhagan
V. Aggarwal
Aaditya Kumar Singh
Sunav Choudhary
FedML
384
1,108
0
02 Dec 2019
Scalable Extreme Deconvolution
Scalable Extreme Deconvolution
James A. Ritchie
Iain Murray
98
1
0
26 Nov 2019
Automatic Differentiable Monte Carlo: Theory and Application
Automatic Differentiable Monte Carlo: Theory and ApplicationPhysical Review Research (PRR), 2019
Shi-Xin Zhang
Z. Wan
H. Yao
160
18
0
20 Nov 2019
Layer-wise Adaptive Gradient Sparsification for Distributed Deep
  Learning with Convergence Guarantees
Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence GuaranteesEuropean Conference on Artificial Intelligence (ECAI), 2019
Shaoshuai Shi
Zhenheng Tang
Qiang-qiang Wang
Kaiyong Zhao
Xiaowen Chu
293
28
0
20 Nov 2019
On the Discrepancy between the Theoretical Analysis and Practical
  Implementations of Compressed Communication for Distributed Deep Learning
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep LearningAAAI Conference on Artificial Intelligence (AAAI), 2019
Aritra Dutta
El Houcine Bergou
A. Abdelmoniem
Chen-Yu Ho
Atal Narayan Sahu
Marco Canini
Panos Kalnis
162
87
0
19 Nov 2019
Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for
  Non Convex Optimization
Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for Non Convex Optimization
Anas Barakat
Pascal Bianchi
186
12
0
18 Nov 2019
Optimal Mini-Batch Size Selection for Fast Gradient Descent
Optimal Mini-Batch Size Selection for Fast Gradient Descent
M. Perrone
Haidar Khan
Changhoan Kim
Anastasios Kyrillidis
Jerry Quinn
V. Salapura
112
9
0
15 Nov 2019
Convergence to minima for the continuous version of Backtracking
  Gradient Descent
Convergence to minima for the continuous version of Backtracking Gradient Descent
T. Truong
136
18
0
11 Nov 2019
Asynchronous Online Federated Learning for Edge Devices with Non-IID
  Data
Asynchronous Online Federated Learning for Edge Devices with Non-IID Data
Yujing Chen
Yue Ning
Martin Slawski
Huzefa Rangwala
FedML
299
57
0
05 Nov 2019
A Rule for Gradient Estimator Selection, with an Application to
  Variational Inference
A Rule for Gradient Estimator Selection, with an Application to Variational InferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Tomas Geffner
Justin Domke
112
6
0
05 Nov 2019
Persistency of Excitation for Robustness of Neural Networks
Persistency of Excitation for Robustness of Neural Networks
Kamil Nar
S. Shankar Sastry
AAML
122
13
0
04 Nov 2019
On the Convergence of Local Descent Methods in Federated Learning
On the Convergence of Local Descent Methods in Federated Learning
Farzin Haddadpour
M. Mahdavi
FedML
274
305
0
31 Oct 2019
Lsh-sampling Breaks the Computation Chicken-and-egg Loop in Adaptive
  Stochastic Gradient Estimation
Lsh-sampling Breaks the Computation Chicken-and-egg Loop in Adaptive Stochastic Gradient Estimation
Beidi Chen
Yingchen Xu
Anshumali Shrivastava
158
16
0
30 Oct 2019
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive
  Synchronization
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive SynchronizationNeural Information Processing Systems (NeurIPS), 2019
Farzin Haddadpour
Mohammad Mahdi Kamani
M. Mahdavi
V. Cadambe
FedML
275
218
0
30 Oct 2019
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks
LeanConvNets: Low-cost Yet Effective Convolutional Neural NetworksIEEE Journal on Selected Topics in Signal Processing (JSTSP), 2019
Jonathan Ephrath
Moshe Eliasof
Lars Ruthotto
E. Haber
Eran Treister
294
18
0
29 Oct 2019
ROCKET: Exceptionally fast and accurate time series classification using
  random convolutional kernels
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernelsData mining and knowledge discovery (DMKD), 2019
Angus Dempster
Franccois Petitjean
Geoffrey I. Webb
AI4TS
209
950
0
29 Oct 2019
Non-Gaussianity of Stochastic Gradient Noise
Non-Gaussianity of Stochastic Gradient Noise
A. Panigrahi
Raghav Somani
Navin Goyal
Praneeth Netrapalli
178
56
0
21 Oct 2019
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