gradient sparsification

RCMoE: A Communication-Efficient Random Compression Framework for Resource-Constrained Mixture-of-Experts Training AAAI 2026 Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning ICML 2024 JointSQ: Joint Sparsification-Quantization for Distributed Learning CVPR 2024 DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks ICML 2022 Dynamic Forward and Backward Sparse Training (DFBST): Accelerated Deep Learning through Completely Sparse Training Schedule ACML 2022 DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning NeurIPS 2021 FLAME: Differentially Private Federated Learning in the Shuffle Model AAAI 2021 Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients NeurIPS 2021 Rethinking gradient sparsification as total error minimization NeurIPS 2021 ReSprop: Reuse Sparsified Backpropagation CVPR 2020 A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification IJCAI 2019 Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations NeurIPS 2019 A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication NeurIPS 2018 Gradient Sparsification for Communication-Efficient Distributed Optimization NeurIPS 2018 Sparsified SGD with Memory NeurIPS 2018 The Convergence of Sparsified Gradient Methods NeurIPS 2018 meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting ICML 2017