conftrace_

distributed training

188 papers

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Co-occurring keywords

distributed learning (563) communication efficiency (297) model parallelism (43) stochastic gradient descent (1091) gradient compression (78) neural network optimization (1293) federated learning (1333) large language model (13587) model compression (3302) neural network (6616)

Papers

SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition JMLR 2019
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems AISTATS 2019
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation NIPS 2019
Learning Generalizable Device Placement Algorithms for Distributed Machine Learning NIPS 2019
fairseq: A Fast, Extensible Toolkit for Sequence Modeling NAACL 2019
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism NIPS 2019
Deep Leakage from Gradients NIPS 2019
Communication trade-offs for Local-SGD with large step size NIPS 2019
Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training EMNLP 2019
Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks CVPR 2019
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning AAAI 2019
Scalable Distributed DL Training: Batching Communication and Computation AAAI 2019
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models NIPS 2019
Fault Tolerance in Iterative-Convergent Machine Learning ICML 2019
FreeFlow: Software-based Virtual RDMA Networking for Containerized Clouds NSDI 2019
Tiresias: A GPU Cluster Manager for Distributed Deep Learning NSDI 2019
FABA: An Algorithm for Fast Aggregation against Byzantine Attacks in Distributed Neural Networks IJCAI 2019
Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent IJCAI 2019
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks ICML 2018
Post: Device Placement with Cross-Entropy Minimization and Proximal Policy Optimization NIPS 2018
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training NIPS 2018
GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning CORL 2018
Accelerating Asynchronous Stochastic Gradient Descent for Neural Machine Translation EMNLP 2018
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training NIPS 2018
Snap ML: A Hierarchical Framework for Machine Learning NIPS 2018