← Optimization & Theory
Machine Learning › Optimization & Theory ›

Distributed Learning

1100 directly classified papers

Papers per year

Papers

A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning AAAI 2020
Randomized Block-Diagonal Preconditioning for Parallel Learning ICML 2020
Moniqua: Modulo Quantized Communication in Decentralized SGD ICML 2020
CSER: Communication-efficient SGD with Error Reset NIPS 2020
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization NIPS 2020
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit COLT 2020
Resilient Distributed Diffusion for Multi-Robot Systems Using Centerpoint RSS 2020
Assise: Performance and Availability via Client-local NVM in a Distributed File System OSDI 2020
Write Dependency Disentanglement with HORAE OSDI 2020
Pegasus: Tolerating Skewed Workloads in Distributed Storage with In-Network Coherence Directories OSDI 2020
On the Acceleration of Deep Learning Model Parallelism With Staleness CVPR 2020
Bundle Adjustment on a Graph Processor CVPR 2020
A Double Residual Compression Algorithm for Efficient Distributed Learning AISTATS 2020
The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits AISTATS 2020
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy AISTATS 2020
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data CVPR 2020
Distributed Machine Learning through Heterogeneous Edge Systems AAAI 2020
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs AISTATS 2020
Decentralized gradient methods: does topology matter? AISTATS 2020
Distributed Stochastic Gradient Descent with Event-Triggered Communication AAAI 2020
Tighter Theory for Local SGD on Identical and Heterogeneous Data AISTATS 2020
How To Backdoor Federated Learning AISTATS 2020
Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models EMNLP 2020
Scalable Belief Propagation via Relaxed Scheduling NIPS 2020
Distributed Primal-Dual Optimization for Online Multi-Task Learning AAAI 2020