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Optimization Methods for Large-Scale Machine Learning

15 June 2016

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

50 / 1,485 papers shown

Title
Continual Learning: Forget-free Winning Subnetworks for Video Representations Haeyong Kang Jaehong Yoon Sung Ju Hwang Chang D. Yoo CLL 428 5 0 19 Dec 2023
DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations Efstathia Soufleri Gang Yan Maroun Touma Jian Li 207 9 0 17 Dec 2023
Physics-Informed Deep Learning of Rate-and-State Fault FrictionComputer Methods in Applied Mechanics and Engineering (CMAME), 2023 Cody Rucker Brittany A. Erickson PINN AI4CE 203 14 0 14 Dec 2023
Layered Randomized Quantization for Communication-Efficient and Privacy-Preserving Distributed Learning Guangfeng Yan Tan Li Tian-Shing Lan Kui Wu Linqi Song 195 9 0 12 Dec 2023
An $LDL^T$ Trust-Region Quasi-Newton Method John Brust Philip E. Gill 47 0 0 11 Dec 2023
ELSA: Partial Weight Freezing for Overhead-Free Sparse Network Deployment Paniz Halvachi Alexandra Peste Dan Alistarh Christoph H. Lampert 126 0 0 11 Dec 2023
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation Rui Ye Yaxin Du Zhenyang Ni Siheng Chen Yanfeng Wang FedML 133 8 0 10 Dec 2023
TaskMet: Task-Driven Metric Learning for Model LearningNeural Information Processing Systems (NeurIPS), 2023 Dishank Bansal Ricky T. Q. Chen Mustafa Mukadam Brandon Amos FedML 232 15 0 08 Dec 2023
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and ApplicationsJournal of Optimization Theory and Applications (JOTA), 2023 Rajeeva Laxman Karandikar M. Vidyasagar 271 17 0 05 Dec 2023
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization Junwen Qiu Xiao Li Andre Milzarek 445 3 0 02 Dec 2023
On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations Antoine Godichon-Baggioni Nicklas Werge ODL 231 4 0 29 Nov 2023
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent Frederik Köhne Leonie Kreis Anton Schiela Roland A. Herzog 245 2 0 28 Nov 2023
SensLI: Sensitivity-Based Layer Insertion for Neural Networks Evelyn Herberg Roland A. Herzog Frederik Köhne Leonie Kreis Anton Schiela 150 0 0 27 Nov 2023
Transformer-based Named Entity Recognition in Construction Supply Chain Risk Management in AustraliaIEEE Access (IEEE Access), 2023 Milad Baghalzadeh Shishehgarkhaneh R. Moehler Yihai Fang Amer A. Hijazi Hamed Aboutorab 239 15 0 23 Nov 2023
Soft Random Sampling: A Theoretical and Empirical Analysis Xiaodong Cui Ashish R. Mittal Songtao Lu Wei Zhang G. Saon Brian Kingsbury 212 2 0 21 Nov 2023
Infinite forecast combinations based on Dirichlet process Yinuo Ren Feng Li Yanfei Kang Jue Wang AI4TS 157 0 0 21 Nov 2023
High Probability Guarantees for Random Reshuffling Hengxu Yu Xiao Li 253 3 0 20 Nov 2023
Using Stochastic Gradient Descent to Smooth Nonconvex Functions: Analysis of Implicit Graduated Optimization with Optimal Noise Scheduling Naoki Sato Hideaki Iiduka 312 4 0 15 Nov 2023
Non-Uniform Smoothness for Gradient Descent A. Berahas Lindon Roberts Fred Roosta 143 5 0 15 Nov 2023
Robust softmax aggregation on blockchain based federated learning with convergence guarantee Huiyu Wu Diego Klabjan FedML 219 3 0 13 Nov 2023
Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization Gabriele Dragotto Stefan Clarke J. F. Fisac Bartolomeo Stellato 412 7 0 06 Nov 2023
Parameter-Agnostic Optimization under Relaxed SmoothnessInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Florian Hübler Junchi Yang Xiang Li Niao He 228 27 0 06 Nov 2023
Signal Processing Meets SGD: From Momentum to Filter Zhipeng Yao Guisong Chang Jiaqi Zhang Qi Zhang Dazhou Li Yu Zhang ODL 508 0 0 06 Nov 2023
High Probability Convergence of Adam Under Unbounded Gradients and Affine Variance Noise Yusu Hong Junhong Lin 169 11 0 03 Nov 2023
Learning to optimize by multi-gradient for multi-objective optimization Linxi Yang Xinmin Yang L. Tang 228 1 0 01 Nov 2023
Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization Philipp Dahlinger P. Becker Maximilian Hüttenrauch Gerhard Neumann 108 0 0 31 Oct 2023
High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise Aleksandar Armacki Pranay Sharma Gauri Joshi Dragana Bajović D. Jakovetić S. Kar 554 10 0 28 Oct 2023
Optimization of utility-based shortfall risk: A non-asymptotic viewpointIEEE Conference on Decision and Control (CDC), 2023 Sumedh Gupte A. PrashanthL. Sanjay P. Bhat 140 2 0 28 Oct 2023
Contextual Stochastic Bilevel OptimizationNeural Information Processing Systems (NeurIPS), 2023 Yifan Hu Jie Wang Yao Xie Andreas Krause Daniel Kuhn 152 18 0 27 Oct 2023
Performative Prediction: Past and FutureStatistical Science (Statist. Sci.), 2023 Moritz Hardt Celestine Mendler-Dünner 319 38 0 25 Oct 2023
Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz Tao Sun Congliang Chen Peng Qiao Li Shen Xinwang Liu Dongsheng Li 157 6 0 23 Oct 2023
Graph Neural Networks and Applied Linear Algebra Nicholas S. Moore Eric C. Cyr Peter Ohm C. Siefert R. Tuminaro 195 6 0 21 Oct 2023
Exponential weight averaging as damped harmonic motion J. Patsenker Henry Li Y. Kluger 163 0 0 20 Oct 2023
DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset Weijie Liu Xiaoxi Zhang Jingpu Duan Carlee Joe-Wong Zhi Zhou Xu Chen 173 19 0 20 Oct 2023
Demystifying the Myths and Legends of Nonconvex Convergence of SGD Aritra Dutta El Houcine Bergou Soumia Boucherouite Nicklas Werge M. Kandemir Xin Li 207 1 0 19 Oct 2023
LASER: Linear Compression in Wireless Distributed Optimization Ashok Vardhan Makkuva Marco Bondaschi Thijs Vogels Martin Jaggi Hyeji Kim Michael C. Gastpar 304 6 0 19 Oct 2023
ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language ModelsInternational Conference on Machine Learning (ICML), 2023 Ziniu Li Tian Xu Yushun Zhang Zhihang Lin Yang Yu Tian Ding Zhimin Luo 299 119 0 16 Oct 2023
Over-the-Air Federated Learning and Optimization Jingyang Zhu Yuanming Shi Yong Zhou Chunxiao Jiang Wei Chen Khaled B. Letaief FedML 357 21 0 16 Oct 2023
Federated Multi-Objective Learning Haibo Yang Zhuqing Liu Jia-Wei Liu Chaosheng Dong Michinari Momma FedML 180 18 0 15 Oct 2023
Fast Sampling and Inference via Preconditioned Langevin Dynamics Riddhiman Bhattacharya Tiefeng Jiang 110 3 0 11 Oct 2023
Quantum Shadow Gradient Descent for Quantum Learning Mohsen Heidari M. Naved Wenbo Xie Arjun Jacob Grama Wojtek Szpankowski 119 0 0 10 Oct 2023
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization Cong Ma Xingyu Xu Tian Tong Yuejie Chi 220 12 0 09 Oct 2023
Learning Layer-wise Equivariances Automatically using GradientsNeural Information Processing Systems (NeurIPS), 2023 Tycho F. A. van der Ouderaa Alexander Immer Mark van der Wilk MLT 228 19 0 09 Oct 2023
On the Parallel Complexity of Multilevel Monte Carlo in Stochastic Gradient Descent Kei Ishikawa BDL 217 0 0 03 Oct 2023
Epidemic Learning: Boosting Decentralized Learning with Randomized CommunicationNeural Information Processing Systems (NeurIPS), 2023 M. Vos Sadegh Farhadkhani R. Guerraoui Anne-Marie Kermarrec Rafael Pires Rishi Sharma 231 24 0 03 Oct 2023
Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoisingJournal of Mathematical Imaging and Vision (JMIV), 2023 Hui Shi Yann Traonmilin Jean-François Aujol 157 1 0 02 Oct 2023
A Theoretical Analysis of Noise Geometry in Stochastic Gradient Descent Mingze Wang Lei Wu 321 3 0 01 Oct 2023
Robust Stochastic Optimization via Gradient Quantile Clipping Ibrahim Merad Stéphane Gaïffas 158 3 0 29 Sep 2023
High Throughput Training of Deep Surrogates from Large Ensemble RunsInternational Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2023 Lucas Meyer M. Schouler R. Caulk Alejandro Ribés Bruno Raffin AI4CE 129 7 0 28 Sep 2023
Enhancing Sharpness-Aware Optimization Through Variance SuppressionNeural Information Processing Systems (NeurIPS), 2023 Bingcong Li G. Giannakis AAML 296 31 0 27 Sep 2023