Distributed Learning
1,202 papers
Papers per year
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27
24
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72
99
115
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115
33
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Papers
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices
NeurIPS 2021
Multi-agent Approach to Resource Allocation in Autonomous Vehicle Fleets
IJCAI 2021
Multi-Institutional Collaborations for Improving Deep Learning-Based Magnetic Resonance Image Reconstruction Using Federated Learning
CVPR 2021
Newton Method over Networks is Fast up to the Statistical Precision
ICML 2021
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization
JMLR 2021
One More Step Towards Reality: Cooperative Bandits with Imperfect Communication
NeurIPS 2021
One-Round Communication Efficient Distributed M-Estimation
AISTATS 2021
On Large-Cohort Training for Federated Learning
NeurIPS 2021
On the Convergence of Communication-Efficient Local SGD for Federated Learning
AAAI 2021
Oort: Efficient Federated Learning via Guided Participant Selection
OSDI 2021
Optimal Complexity in Decentralized Training
ICML 2021
Optimal Rates of Distributed Regression with Imperfect Kernels
JMLR 2021
P3: Distributed Deep Graph Learning at Scale
OSDI 2021
Parallel and Efficient Hierarchical k-Median Clustering
NeurIPS 2021
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
ICML 2021
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning
OSDI 2021
Preserved central model for faster bidirectional compression in distributed settings
NeurIPS 2021
Privacy-Preserving Voice Anti-Spoofing Using Secure Multi-Party Computation
Interspeech 2021
Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains (Demo)
AAAI 2021
Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
ICML 2021
RelaySum for Decentralized Deep Learning on Heterogeneous Data
NeurIPS 2021
Rethinking gradient sparsification as total error minimization
NeurIPS 2021
Revealing and Protecting Labels in Distributed Training
NeurIPS 2021
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem
NeurIPS 2021
Scaling Distributed Machine Learning with In-Network Aggregation
NSDI 2021