parallel training

Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures NeurIPS 2020 Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks ICML 2020 On the Acceleration of Deep Learning Model Parallelism With Staleness CVPR 2020 Sideways: Depth-Parallel Training of Video Models CVPR 2020 Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models EMNLP 2020 Stochastic Weight Averaging in Parallel: Large-Batch Training That Generalizes Well ICLR 2020 Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning AAAI 2019 SVM-Based Deep Stacking Networks AAAI 2019 Bayesian Distributed Stochastic Gradient Descent NeurIPS 2018 BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training NeurIPS 2018 Decoupled Parallel Backpropagation with Convergence Guarantee ICML 2018 Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training NeurIPS 2018 Training Neural Networks Using Features Replay NeurIPS 2018 Empirical Evaluation of Parallel Training Algorithms on Acoustic Modeling Interspeech 2017 Fast Parallel Training of Neural Language Models IJCAI 2017 Hard Mixtures of Experts for Large Scale Weakly Supervised Vision CVPR 2017 Speeding up Reinforcement Learning-based Information Extraction Training using Asynchronous Methods EMNLP 2017 Deep learning with Elastic Averaging SGD NeurIPS 2015 Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training ICML 2013