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Distributed Learning

157 papers

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Papers

Accelerated Methods with Compressed Communications for Distributed Optimization Problems Under Data Similarity AAAI 2025
Scalable Decentralized Algorithms for Online Personalized Mean Estimation AAAI 2025
Asynchronous Distributed Gaussian Process Regression AAAI 2025
Decentralized Diffusion Models CVPR 2025
A Decentralized Proximal Gradient Tracking Algorithm for Composite Optimization on Riemannian Manifolds JMLR 2025
Optimal and Efficient Algorithms for Decentralized Online Convex Optimization JMLR 2025
EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback JMLR 2025
Decentralized Asynchronous Optimization with DADAO allows Decoupling and Acceleration JMLR 2025
Optimal Decentralized Composite Optimization for Strongly Convex Functions JMLR 2025
ZEN: Empowering Distributed Training with Sparsity-driven Data Synchronization OSDI 2025
Implicit Regularization of Decentralized Gradient Descent for Sparse Regression NIPS 2024
Ordered Momentum for Asynchronous SGD NIPS 2024
Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes NIPS 2024
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity NIPS 2024
Exponential Quantum Communication Advantage in Distributed Inference and Learning NIPS 2024
LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing NIPS 2024
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations NIPS 2024
Leveraging partial stragglers within gradient coding NIPS 2024
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization NIPS 2024
Distributed Least Squares in Small Space via Sketching and Bias Reduction NIPS 2024
Beyond Single Stationary Policies: Meta-Task Players as Naturally Superior Collaborators NIPS 2024
Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences NIPS 2024
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs NIPS 2024
Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity NIPS 2024
SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization NIPS 2024