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Distributed Optimization

99 directly classified papers

Papers per year

Papers

PA3Fed: Period-Aware Adaptive Aggregation for Improved Federated Learning AAAI 2025
Accelerated Methods with Compressed Communications for Distributed Optimization Problems Under Data Similarity AAAI 2025
Scalable Decentralized Algorithms for Online Personalized Mean Estimation AAAI 2025
The Sample-Communication Complexity Trade-off in Federated Q-Learning NIPS 2024
iMESA: Incremental Distributed Optimization for Collaborative Simultaneous Localization and Mapping RSS 2024
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations NIPS 2024
SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization NIPS 2024
Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity NIPS 2024
Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences NIPS 2024
Distributed Least Squares in Small Space via Sketching and Bias Reduction NIPS 2024
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization NIPS 2024
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity NIPS 2024
Leveraging partial stragglers within gradient coding NIPS 2024
Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization NIPS 2023
Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory AAAI 2023
Optimal Shrinkage for Distributed Second-Order Optimization ICML 2023
Distributed Projection-Free Online Learning for Smooth and Convex Losses AAAI 2023
Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm NIPS 2023
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework AAAI 2023
Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization AAAI 2023
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? NIPS 2023
$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning NIPS 2023
Beyond Spectral Gap: The Role of the Topology in Decentralized Learning JMLR 2023
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM NIPS 2023
Distributed Bundle Adjustment with Block-Based Sparse Matrix Compression for Super Large Scale Datasets ICCV 2023