Distributed Learning

GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning JMLR 2020 Gap-Aware Mitigation of Gradient Staleness ICLR 2020 Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent JMLR 2020 Gryff: Unifying Consensus and Shared Registers NSDI 2020 How To Backdoor Federated Learning AISTATS 2020 IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method NeurIPS 2020 IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks ICLR 2020 Improved Communication Cost in Distributed PageRank Computation – A Theoretical Study ICML 2020 Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking ICML 2020 Indirect Stochastic Gradient Quantization and Its Application in Distributed Deep Learning AAAI 2020 Is Local SGD Better than Minibatch SGD? ICML 2020 Knowledge Base Embedding By Cooperative Knowledge Distillation COLING 2020 KungFu: Making Training in Distributed Machine Learning Adaptive OSDI 2020 Linearly Converging Error Compensated SGD NeurIPS 2020 Lower Bounds and Optimal Algorithms for Personalized Federated Learning NeurIPS 2020 Manifold Identification for Ultimately Communication-Efficient Distributed Optimization ICML 2020 Millions of Tiny Databases NSDI 2020 Moniqua: Modulo Quantized Communication in Decentralized SGD ICML 2020 Mutual Transfer Learning for Massive Data ICML 2020 Near-Optimal Latency Versus Cost Tradeoffs in Geo-Distributed Storage NSDI 2020 One-shot Distributed Ridge Regression in High Dimensions ICML 2020 Online Convex Optimization Over Erdos-Renyi Random Networks NeurIPS 2020 On the Acceleration of Deep Learning Model Parallelism With Staleness CVPR 2020 On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning AAAI 2020 Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization NeurIPS 2020