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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
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Distributed Learning
1100 directly classified papers
Papers per year
2006: 1
2007: 3
2008: 3
2009: 5
2010: 6
2011: 4
2012: 9
2013: 20
2014: 27
2015: 18
2016: 44
2017: 49
2018: 70
2019: 92
2020: 108
2021: 125
2022: 127
2023: 145
2024: 125
2025: 89
2026: 30
Papers
SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning
NIPS 2022
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations
NIPS 2022
Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums
ICML 2022
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation
AAAI 2022
Closing the Generalization Gap of Cross-Silo Federated Medical Image Segmentation
CVPR 2022
Resilient and Communication Efficient Learning for Heterogeneous Federated Systems
ICML 2022
DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks
ICML 2022
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
AAAI 2022
Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information
L4DC 2022
Learning Linear Models Using Distributed Iterative Hessian Sketching
L4DC 2022
Asynchronous Personalized Federated Learning with Irregular Clients
ACML 2022
Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate
NIPS 2022
Towards Optimal Communication Complexity in Distributed Non-Convex Optimization
NIPS 2022
Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and Parallelization
OSDI 2022
Acceleration in Distributed Sparse Regression
NIPS 2022
Robust Combination of Distributed Gradients Under Adversarial Perturbations
CVPR 2022
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression
NIPS 2021
Communication-efficient SGD: From Local SGD to One-Shot Averaging
NIPS 2021
Distributed Principal Component Analysis with Limited Communication
NIPS 2021
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation
NIPS 2021
Error Compensated Distributed SGD Can Be Accelerated
NIPS 2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
NIPS 2021
Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback
NIPS 2021
One More Step Towards Reality: Cooperative Bandits with Imperfect Communication
NIPS 2021
Asynchronous Decentralized SGD with Quantized and Local Updates
NIPS 2021
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