← Optimization & Theory
Machine Learning › Optimization & Theory ›

Distributed Learning

1100 directly classified papers

Papers per year

Papers

GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization ICCV 2023
Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning UAI 2023
Robust Heterogeneous Federated Learning under Data Corruption ICCV 2023
Scalable Distributed Massive MIMO Baseband Processing NSDI 2023
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond ICML 2023
zPROBE: Zero Peek Robustness Checks for Federated Learning ICCV 2023
Distributed Inference and Fine-tuning of Large Language Models Over The Internet NIPS 2023
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks ICML 2023
TACCL: Guiding Collective Algorithm Synthesis using Communication Sketches NSDI 2023
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices NIPS 2023
Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks (Extended Abstract) IJCAI 2023
Fast Algorithms for Distributed k-Clustering with Outliers ICML 2023
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization NIPS 2023
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning NIPS 2023
Modeling with Homophily Driven Heterogeneous Data in Gossip Learning IJCAI 2023
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems NIPS 2023
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis NIPS 2023
Birder: Communication-Efficient 1-bit Adaptive Optimizer for Practical Distributed DNN Training NIPS 2023
Optimal Shrinkage for Distributed Second-Order Optimization ICML 2023
EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression ICML 2023
Better Together: Jointly Optimizing ML Collective Scheduling and Execution Planning using SYNDICATE NSDI 2023
$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning NIPS 2023
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy NIPS 2023
A one-sample decentralized proximal algorithm for non-convex stochastic composite optimization UAI 2023
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence NIPS 2023