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distributed learning

563 papers

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Also known as

DL-DCL DML

Co-occurring keywords

federated learning (1320) stochastic gradient descent (1088) communication efficiency (297) distributed optimization (275) stochastic optimization (1060) decentralized optimization (113) communication complexity (99) distributed training (187) gradient compression (78) gradient descent (1143)

Papers

Secure Distributed Sparse Gaussian Process Models Using Multi-Key Homomorphic Encryption AAAI 2024
The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication COLT 2024
Distributed Algorithms for U-statistics-based Empirical Risk Minimization JMLR 2023
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates JMLR 2023
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD JMLR 2023
Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data JMLR 2023
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks ICML 2023
Understanding Deep Gradient Leakage via Inversion Influence Functions NIPS 2023
Better Together: Jointly Optimizing ML Collective Scheduling and Execution Planning using SYNDICATE NSDI 2023
Re-Thinking Federated Active Learning Based on Inter-Class Diversity CVPR 2023
Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks (Extended Abstract) IJCAI 2023
Incremental Aggregated Riemannian Gradient Method for Distributed PCA AISTATS 2023
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems AAAI 2023
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication ICML 2023
Network Effects in Performative Prediction Games ICML 2023
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning ICML 2023
Differentially Private Distributed Bayesian Linear Regression with MCMC ICML 2023
Distributed Projection-Free Online Learning for Smooth and Convex Losses AAAI 2023
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning AAAI 2023
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods AISTATS 2023
MAS: Towards Resource-Efficient Federated Multiple-Task Learning ICCV 2023
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning AAAI 2023
Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization ICCV 2023
Robust Heterogeneous Federated Learning under Data Corruption ICCV 2023
Federated Generative Model on Multi-Source Heterogeneous Data in IoT AAAI 2023