Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms

22 June 2015

Papers citing "Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms"

33 / 33 papers shown

Title
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees Ali Ramezani-Kebrya Kimon Antonakopoulos Igor Krawczuk Justin Deschenaux V. Cevher 36 3 0 17 Aug 2023
Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression Boyue Li Yuejie Chi 21 12 0 17 May 2023
Considerations on the Theory of Training Models with Differential Privacy Marten van Dijk Phuong Ha Nguyen FedML 31 2 0 08 Mar 2023
Quantization-Based Optimization: Alternative Stochastic Approximation of Global Optimization Jinwuk Seok Changhun Cho 16 2 0 08 Nov 2022
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud Zhen Zhang Shuai Zheng Yida Wang Justin Chiu George Karypis Trishul Chilimbi Mu Li Xin Jin 19 39 0 30 Apr 2022
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization Kaiwen Zhou Anthony Man-Cho So James Cheng 19 1 0 30 Sep 2021
An optical neural network using less than 1 photon per multiplication Tianyu Wang Shifan Ma Logan G. Wright Tatsuhiro Onodera Brian C. Richard Peter L. McMahon 50 177 0 27 Apr 2021
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation Wei Ping Fan Wu Yunhui Long Luka Rimanic Ce Zhang Bo-wen Li FedML 45 63 0 20 Mar 2021
Consistent Lock-free Parallel Stochastic Gradient Descent for Fast and Stable Convergence Karl Bäckström Ivan Walulya Marina Papatriantafilou P. Tsigas 29 5 0 17 Feb 2021
Integrating Deep Learning in Domain Sciences at Exascale Rick Archibald E. Chow E. DÁzevedo Jack J. Dongarra M. Eisenbach ... Florent Lopez Daniel Nichols S. Tomov Kwai Wong Junqi Yin PINN 23 5 0 23 Nov 2020
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 42 10 0 27 Oct 2020
Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research A. Feder Cooper 10 7 0 20 Oct 2020
Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs A. Rajagopal D. A. Vink Stylianos I. Venieris C. Bouganis MQ 16 14 0 16 Jun 2020
MixML: A Unified Analysis of Weakly Consistent Parallel Learning Yucheng Lu J. Nash Christopher De Sa FedML 32 12 0 14 May 2020
On-Device Machine Learning: An Algorithms and Learning Theory Perspective Sauptik Dhar Junyao Guo Jiayi Liu S. Tripathi Unmesh Kurup Mohak Shah 28 141 0 02 Nov 2019
JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training José Á. Morell Andrés Camero Enrique Alba 26 9 0 12 Oct 2019
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free Mingrui Zhang Lin Chen Aryan Mokhtari Hamed Hassani Amin Karbasi 16 8 0 17 Feb 2019
HOGWILD!-Gibbs can be PanAccurate C. Daskalakis Nishanth Dikkala S. Jayanti 16 13 0 26 Nov 2018
New Convergence Aspects of Stochastic Gradient Algorithms Lam M. Nguyen Phuong Ha Nguyen Peter Richtárik K. Scheinberg Martin Takáč Marten van Dijk 23 66 0 10 Nov 2018
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 79 1,044 0 24 May 2018
Eigenvector Computation and Community Detection in Asynchronous Gossip Models Frederik Mallmann-Trenn Cameron Musco Christopher Musco 23 9 0 23 Apr 2018
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis Tal Ben-Nun Torsten Hoefler GNN 33 702 0 26 Feb 2018
SparCML: High-Performance Sparse Communication for Machine Learning Cédric Renggli Saleh Ashkboos Mehdi Aghagolzadeh Dan Alistarh Torsten Hoefler 29 126 0 22 Feb 2018
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption Lam M. Nguyen Phuong Ha Nguyen Marten van Dijk Peter Richtárik K. Scheinberg Martin Takáč 33 226 0 11 Feb 2018
Improved asynchronous parallel optimization analysis for stochastic incremental methods Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien 16 70 0 11 Jan 2018
Gradient Sparsification for Communication-Efficient Distributed Optimization Jianqiao Wangni Jialei Wang Ji Liu Tong Zhang 15 522 0 26 Oct 2017
GPU-acceleration for Large-scale Tree Boosting Huan Zhang Si Si Cho-Jui Hsieh 16 80 0 26 Jun 2017
Exploring the Design Space of Deep Convolutional Neural Networks at Large Scale F. Iandola 3DV 26 18 0 20 Dec 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 66 1,878 0 08 Oct 2016
ASAGA: Asynchronous Parallel SAGA Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien AI4TS 29 101 0 15 Jun 2016
Fast Zero-Shot Image Tagging Yang Zhang Boqing Gong M. Shah VLM 3DV 19 141 0 31 May 2016
Level Up Your Strategy: Towards a Descriptive Framework for Meaningful Enterprise Gamification Xinghao Pan 29 62 0 29 May 2016
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling Christopher De Sa K. Olukotun Christopher Ré 16 51 0 24 Feb 2016