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← Optimization & Theory
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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
Communication-Computation Efficient Gradient Coding
ICML 2018
Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters
NIPS 2018
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
ICML 2018
$D^2$: Decentralized Training over Decentralized Data
ICML 2018
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
ICML 2018
Distributed Self-Paced Learning in Alternating Direction Method of Multipliers
IJCAI 2018
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
ICML 2018
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
ICML 2018
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
ICML 2018
Asynchronous Decentralized Parallel Stochastic Gradient Descent
ICML 2018
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
AISTATS 2018
Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation
AISTATS 2018
Distributed Weight Consolidation: A Brain Segmentation Case Study
NIPS 2018
Distributing Frank-Wolfe via Map-Reduce
IJCAI 2018
Convergence Analysis of Distributed Inference with Vector-Valued Gaussian Belief Propagation
JMLR 2018
An efficient distributed learning algorithm based on effective local functional approximations
JMLR 2018
Parallel Bayesian Network Structure Learning
ICML 2018
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
ICML 2018
The Hidden Vulnerability of Distributed Learning in Byzantium
ICML 2018
signSGD: Compressed Optimisation for Non-Convex Problems
ICML 2018
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
ICML 2018
Mesh-TensorFlow: Deep Learning for Supercomputers
NIPS 2018
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
ICML 2018
Distributed Nonparametric Regression under Communication Constraints
ICML 2018
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
ICML 2018
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