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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
Asynchronous Personalized Federated Learning with Irregular Clients
ACML 2022
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation
AAAI 2022
Robust Combination of Distributed Gradients Under Adversarial Perturbations
CVPR 2022
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees
NIPS 2022
EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles
AAAI 2022
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
AAAI 2022
Federated Learning for Face Recognition with Gradient Correction
AAAI 2022
Efficient Decentralized Stochastic Gradient Descent Method for Nonconvex Finite-Sum Optimization Problems
AAAI 2022
Detached Error Feedback for Distributed SGD with Random Sparsification
ICML 2022
Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent
ICML 2022
Interlocking Backpropagation: Improving depthwise model-parallelism
JMLR 2022
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning
AISTATS 2022
Solving Multi-Arm Bandit Using a Few Bits of Communication
AISTATS 2022
Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization
AISTATS 2022
SplitFed: When Federated Learning Meets Split Learning
AAAI 2022
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data
ICML 2022
Privacy Amplification by Decentralization
AISTATS 2022
Byzantine-tolerant distributed multiclass sparse linear discriminant analysis
UAI 2022
Federated Learning with Buffered Asynchronous Aggregation
AISTATS 2022
Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs
NIPS 2022
Personalized Online Federated Learning with Multiple Kernels
NIPS 2022
Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization
JMLR 2022
Distributed Sparse Multicategory Discriminant Analysis
AISTATS 2022
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays
NIPS 2022
Distributed Randomized Sketching Kernel Learning
AAAI 2022
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