communication efficiency

Communication Efficient Distributed Training with Distributed Lion NeurIPS 2024 Communication-Efficient Federated Group Distributionally Robust Optimization NeurIPS 2024 Communication-Efficient Federated Learning with Accelerated Client Gradient CVPR 2024 Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates ICLR 2024 Countering the Communication Bottleneck in Federated Learning: A Highly Efficient Zero-Order Optimization Technique JMLR 2024 DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models CVPR 2024 Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms JMLR 2024 Distributed Least Squares in Small Space via Sketching and Bias Reduction NeurIPS 2024 Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD NeurIPS 2024 ERMVP: Communication-Efficient and Collaboration-Robust Multi-Vehicle Perception in Challenging Environments CVPR 2024 FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models ICML 2024 Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis NeurIPS 2024 Federated Prompt Learning for Weather Foundation Models on Devices IJCAI 2024 FedLFC: Towards Efficient Federated Multilingual Modeling with LoRA-based Language Family Clustering NAACL 2024 FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning AAAI 2024 Implicit Regularization of Decentralized Gradient Descent for Sparse Regression NeurIPS 2024 JointSQ: Joint Sparsification-Quantization for Distributed Learning CVPR 2024 Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning NeurIPS 2024 Low Precision Local Training is Enough for Federated Learning NeurIPS 2024 LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing NeurIPS 2024 Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices CVPR 2024 Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning NAACL 2024 Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models NeurIPS 2024 Revisiting Ensembling in One-Shot Federated Learning NeurIPS 2024 Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks AAAI 2024