Showing 1–20 of 49 results
/ Date/ Name
Oct 3, 2022Taming Fat-Tailed ("Heavier-Tailed'' with Potentially Infinite Variance) Noise in Federated LearningOct 15, 2023Federated Multi-Objective LearningSep 10, 2019Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median ApproachJun 14, 2021CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated LearningJan 27, 2021Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated LearningMay 4, 2024Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client ParticipationAug 23, 2021Anarchic Federated LearningOct 2, 2022SAGDA: Achieving $\mathcal{O}(ε^{-2})$ Communication Complexity in Federated Min-Max LearningSep 28, 2022Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidenceSep 30, 2021Observations of Forbush Decreases of cosmic ray electrons and positrons with the Dark Matter Particle ExplorerJun 19, 2021STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated LearningAug 17, 2022NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous DataFeb 14, 2024Can TM system form an unconditional basis for Banach spaces?Mar 25, 2024VP3D: Unleashing 2D Visual Prompt for Text-to-3D GenerationNov 28, 2025Huizhou Hadron Spectrometer -- a Proposed High-rate Experimental Setup at the High Intensity Heavy-ion Accelerator FacilityJun 24, 2025STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective LearningMay 14, 2025Exploring Pose-Guided Imitation Learning for Robotic Precise InsertionSep 5, 2024Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning?Sep 13, 2024Peetre conjecture on real interpolation spaces of Besov spaces and Grid K functionalJul 29, 2025Enabling Pareto-Stationarity Exploration in Multi-Objective Reinforcement Learning: A Multi-Objective Weighted-Chebyshev Actor-Critic Approach