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Distributed Learning

1100 directly classified papers

Papers per year

Papers

Distributed Estimation on Semi-Supervised Generalized Linear Model JMLR 2024
Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms JMLR 2024
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization JMLR 2024
Human-LLM Hybrid Text Answer Aggregation for Crowd Annotations EMNLP 2024
Implicit Regularization of Decentralized Gradient Descent for Sparse Regression NIPS 2024
KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Server EMNLP 2024
Towards Stability and Generalization Bounds in Decentralized Minibatch Stochastic Gradient Descent AAAI 2024
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models ACL 2024
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update AAAI 2024
CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following ACL 2024
An Empirical Study of Distributed Deep Learning Training on Edge (Student Abstract) AAAI 2024
Cheaper and Faster: Distributed Deep Reinforcement Learning with Serverless Computing AAAI 2024
Byzantine-robust Decentralized Federated Learning via Dual-domain Clustering and Trust Bootstrapping CVPR 2024
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training NIPS 2024
Communication Efficient Distributed Training with Distributed Lion NIPS 2024
Incorporating Serverless Computing into P2P Networks for ML Training: In-Database Tasks and Their Scalability Implications (Student Abstract) AAAI 2024
Decentralized Gradient-Free Methods for Stochastic Non-smooth Non-convex Optimization AAAI 2024
HPipe: Large Language Model Pipeline Parallelism for Long Context on Heterogeneous Cost-effective Devices NAACL 2024
Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with Outliers AAAI 2024
Leveraging partial stragglers within gradient coding NIPS 2024
A deep learning approach for distributed aggregative optimization with users’ Feedback L4DC 2024
Byzantine-Robust Decentralized Learning via Remove-then-Clip Aggregation AAAI 2024
Parallel Empirical Evaluations: Resilience despite Concurrency AAAI 2024
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD NIPS 2024
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning NIPS 2024