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Distributed Mean Estimation with Limited Communication

2 November 2016

Sanjiv Kumar

Papers citing "Distributed Mean Estimation with Limited Communication"

50 / 196 papers shown

Title
CafeQ: Calibration-free Quantization via Learned Transformations and Adaptive Rounding Ziteng Sun Adrian Benton Samuel Kushnir Asher Trockman Vikas Singh Suhas Diggavi A. Suresh MQ 37 0 0 24 Nov 2025
Efficient Covariance Estimation for Sparsified Functional Data Sijie Zheng Fandong Meng Jie Zhou 16 0 0 23 Nov 2025
Low-Precision Streaming PCA Sanjoy Dasgupta Syamantak Kumar Shourya Pandey Purnamrita Sarkar 96 0 0 25 Oct 2025
Unbiased Gradient Low-Rank Projection Rui Pan Yang Luo Yuxing Liu Yang You Tong Zhang 72 0 0 20 Oct 2025
Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity Ivan Lau Jonathan Scarlett 72 1 0 26 Sep 2025
Metis: Training LLMs with FP4 Quantization Hengjie Cao M. Ben-Chen Yifeng Yang Ruijun Huang Fang Dong ... Fan Wu Fan Yang Tun Lu Ning Gu Li Shang MQ 160 1 0 30 Aug 2025
Quartet: Native FP4 Training Can Be Optimal for Large Language Models Roberto L. Castro Andrei Panferov Soroush Tabesh Oliver Sieberling Jiale Chen Mahdi Nikdan Saleh Ashkboos Dan Alistarh MQ 236 6 0 20 May 2025
Convergence Analysis of Asynchronous Federated Learning with Gradient Compression for Non-Convex Optimization Diying Yang Yingwei Hou Danyang Xiao FedML 238 0 0 28 Apr 2025
Distributionally Robust Federated Learning: An ADMM Algorithm Wen Bai Yi Wong Xiao Qiao Chin Pang Ho FedML OOD 250 0 0 24 Mar 2025
PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors Hilal Asi Vitaly Feldman Hannah Keller G. Rothblum Kunal Talwar FedML 312 1 0 14 Mar 2025
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex OptimizationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025 Sudeep Salgia Nikola Pavlovic Yuejie Chi Qing Zhao 240 0 0 06 Jan 2025
Review of Mathematical Optimization in Federated Learning Shusen Yang Fangyuan Zhao Zihao Zhou Liang Shi Xuebin Ren Zongben Xu FedML AI4CE 267 5 0 02 Dec 2024
Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Vladimir Malinovskii Andrei Panferov Ivan Ilin Han Guo Peter Richtárik Dan Alistarh MQ 283 10 0 26 Nov 2024
Overpredictive Signal Analytics in Federated Learning: Algorithms and Analysis Vijay Anavangot FedML 82 0 0 02 Oct 2024
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness Hojat Allah Salehi Md Jueal Mia S. Sandeep Pradhan M. Hadi Amini Farhad Shirani FedML 239 1 0 20 Sep 2024
Federated PCA on Grassmann Manifold for IoT Anomaly Detection Tung-Anh Nguyen Long Tan Le Tuan Dung Nguyen Wei Bao Suranga Seneviratne Choong Seon Hong N. H. Tran 151 14 0 10 Jul 2024
Beyond Throughput and Compression Ratios: Towards High End-to-end Utility of Gradient Compression Wenchen Han S. Vargaftik Michael Mitzenmacher Brad Karp Ran Ben-Basat 141 7 0 01 Jul 2024
FedAQ: Communication-Efficient Federated Edge Learning via Joint Uplink and Downlink Adaptive Quantization Linping Qu Shenghui Song Chi-Ying Tsui MQ FedML 127 5 0 26 Jun 2024
Training Diffusion Models with Federated Learning Matthijs de Goede Bart Cox Jérémie Decouchant FedML 171 14 0 18 Jun 2024
Privacy Preserving Semi-Decentralized Mean Estimation over Intermittently-Connected Networks R. Saha Mohamed Seif M. Yemini Andrea J. Goldsmith H. Vincent Poor FedML 171 5 0 06 Jun 2024
Exploring the Practicality of Federated Learning: A Survey Towards the Communication Perspective Khiem H. Le Nhan Luong-Ha Manh Nguyen-Duc Danh Le-Phuoc Cuong D. Do Kok-Seng Wong FedML 206 6 0 30 May 2024
Universal Exact Compression of Differentially Private Mechanisms Yanxiao Liu Wei-Ning Chen Ayfer Özgür Cheuk Ting Li 173 9 0 28 May 2024
The Effect of Quantization in Federated Learning: A Rényi Differential Privacy PerspectiveInternational Mediterranean Conference on Communications and Networking (MCN), 2024 Tianqu Kang Lumin Liu Hengtao He Jun Zhang Shenghui Song Khaled B. Letaief FedML 102 6 0 16 May 2024
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy Wei-Ning Chen Berivan Isik Peter Kairouz Albert No Sewoong Oh Zheng Xu 247 3 0 02 May 2024
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey Feng Liang Zhen Zhang Haifeng Lu Victor C. M. Leung Yanyi Guo Xiping Hu GNN 247 18 0 09 Apr 2024
Distributed Learning based on 1-Bit Gradient Coding in the Presence of Stragglers Chengxi Li Mikael Skoglund 234 7 0 19 Mar 2024
Efficient Language Model Architectures for Differentially Private Federated Learning Jae Hun Ro Srinadh Bhojanapalli Zheng Xu Yanxiang Zhang A. Suresh FedML 170 3 0 12 Mar 2024
Fed-CVLC: Compressing Federated Learning Communications with Variable-Length CodesIEEE Conference on Computer Communications (INFOCOM), 2024 Xiaoxin Su Yipeng Zhou Laizhong Cui John C. S. Lui Jiangchuan Liu FedML 162 2 0 06 Feb 2024
Optimal and Near-Optimal Adaptive Vector Quantization Ran Ben-Basat Y. Ben-Itzhak Michael Mitzenmacher S. Vargaftik MQ 153 1 0 05 Feb 2024
$L_q$ Lower Bounds on Distributed Estimation via Fisher Information Wei-Ning Chen Ayfer Özgür 142 1 0 02 Feb 2024
Correlated Quantization for Faster Nonconvex Distributed OptimizationConference on Uncertainty in Artificial Intelligence (UAI), 2024 Andrei Panferov Yury Demidovich Ahmad Rammal Peter Richtárik MQ 197 4 0 10 Jan 2024
Federated Hyperdimensional Computing Kazim Ergun Rishikanth Chandrasekaran Tajana Simunic FedML 109 0 0 26 Dec 2023
Kimad: Adaptive Gradient Compression with Bandwidth Awareness Jihao Xin Ivan Ilin Shunkang Zhang Marco Canini Peter Richtárik 172 3 0 13 Dec 2023
Compression with Exact Error Distribution for Federated LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Mahmoud Hegazy Rémi Leluc Cheuk Ting Li Hadrien Hendrikx FedML 142 17 0 31 Oct 2023
Correlation Aware Sparsified Mean Estimation Using Random ProjectionNeural Information Processing Systems (NeurIPS), 2023 Shuli Jiang Pranay Sharma Gauri Joshi 236 2 0 29 Oct 2023
How Robust is Federated Learning to Communication Error? A Comparison Study Between Uplink and Downlink ChannelsIEEE Wireless Communications and Networking Conference (WCNC), 2023 Linping Qu Shenghui Song Chi-Ying Tsui Yuyi Mao 126 3 0 25 Oct 2023
Federated Learning with Nonvacuous Generalisation Bounds Pierre Jobic Maxime Haddouche Benjamin Guedj FedML 204 4 0 17 Oct 2023
Matrix Compression via Randomized Low Rank and Low Precision FactorizationNeural Information Processing Systems (NeurIPS), 2023 R. Saha Varun Srivastava Mert Pilanci 197 30 0 17 Oct 2023
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 244 11 0 15 Oct 2023
Ultima: Robust and Tail-Optimal AllReduce for Distributed Deep Learning in the CloudSymposium on Networked Systems Design and Implementation (NSDI), 2023 Ertza Warraich Omer Shabtai Khalid Manaa S. Vargaftik Y. Piasetzky Matty Kadosh Lalith Suresh Muhammad Shahbaz 96 1 0 10 Oct 2023
Fundamental Limits of Distributed Optimization over Multiple Access ChannelInformation Theory Workshop (ITW), 2023 Shubham K. Jha 147 1 0 05 Oct 2023
Federated Deep Equilibrium Learning: A Compact Shared Representation for Edge Communication EfficiencyInternational Conference on Information and Knowledge Management (CIKM), 2023 Long Tan Le Tuan Dung Nguyen Tung-Anh Nguyen Choong Seon Hong Nguyen H. Tran FedML 197 0 0 27 Sep 2023
Communication Efficient Private Federated Learning Using DitheringIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023 Burak Hasircioglu Deniz Gunduz FedML 225 12 0 14 Sep 2023
Maestro: Uncovering Low-Rank Structures via Trainable DecompositionInternational Conference on Machine Learning (ICML), 2023 Samuel Horváth Stefanos Laskaridis Shashank Rajput Hongyi Wang BDL 262 9 0 28 Aug 2023
Differentially Private Aggregation via Imperfect ShufflingInternational Test Conference (ITC), 2023 Badih Ghazi Ravi Kumar Pasin Manurangsi Jelani Nelson Samson Zhou FedML 248 1 0 28 Aug 2023
Optimal Compression of Unit Norm Vectors in the High Distortion RegimeInternational Symposium on Information Theory (ISIT), 2023 He Zhu Avishek Ghosh A. Mazumdar 120 3 0 16 Jul 2023
Adaptive Compression in Federated Learning via Side InformationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Berivan Isik Francesco Pase Deniz Gunduz Sanmi Koyejo Tsachy Weissman M. Zorzi FedML 136 16 0 22 Jun 2023
Training generative models from privatized dataIEEE Journal on Selected Areas in Information Theory (JSAIT), 2023 Daria Reshetova Wei-Ning Chen Ayfer Özgür FedML 173 4 0 15 Jun 2023
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean EstimationNeural Information Processing Systems (NeurIPS), 2023 Berivan Isik Wei-Ning Chen Ayfer Özgür Tsachy Weissman Albert No 241 21 0 08 Jun 2023
Fast Optimal Locally Private Mean Estimation via Random ProjectionsNeural Information Processing Systems (NeurIPS), 2023 Hilal Asi Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar FedML 199 15 0 07 Jun 2023