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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

MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates NIPS 2023
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods AISTATS 2023
A principled framework for the design and analysis of token algorithms AISTATS 2023
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? ICML 2023
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent ICML 2023
Federated Generative Model on Multi-Source Heterogeneous Data in IoT AAAI 2023
Algorithmic Collective Action in Machine Learning ICML 2023
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm ICML 2023
Federated Learning under Distributed Concept Drift AISTATS 2023
Federated Adversarial Learning: A Framework with Convergence Analysis ICML 2023
Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization ICCV 2023
DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization ICML 2023
Federated Learning for Commercial Image Sources WACV 2023
Buffered Asynchronous SGD for Byzantine Learning JMLR 2023
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems AAAI 2023
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD JMLR 2023
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning IJCAI 2023
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance NIPS 2023
Petals: Collaborative Inference and Fine-tuning of Large Models ACL 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning ICML 2023
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning NIPS 2023
Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning AAAI 2023
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets NIPS 2023
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023
Flash: Concept Drift Adaptation in Federated Learning ICML 2023