conftrace_

convergence guarantee

247 papers

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stochastic gradient descent (29) non-convex optimization (27) gradient descent (24) stochastic optimization (23) federated learning (21) convergence analysis (16) reinforcement learning (16) neural network (10) neural network optimization (10) temporal difference learning (10)

Papers

Achieving Alignment Through Adaptive Play: Helping Optimize Objectives Without Observing Them UAI 2026 A Two-Timescale Primal-Dual Framework for Reinforcement Learning via Online Dual Variable Guidance JMLR 2026 Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions UAI 2026 Convergence of Decentralized Stochastic Subgradient-based Methods for Nonsmooth Nonconvex Optimization JMLR 2026 Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees COLT 2026 Evaluating the Role of Great Pre-trained Diffusion Models in Few-shot Phase: Warm-up and Acceleration UAI 2026 FedAdamom: Adaptive Momentum for Improved Generalization in Federated Optimization CVPR 2026 FedMOP: Achieving Enhanced Privacy and Performance in Federated Learning via Momentum Orthogonal Projection CVPR 2026 First-Order Softmax Weighted Switching Gradient Method for Distributed Stochastic Minimax Optimization with Stochastic Constraints UAI 2026 Fully Decentralized Certified Unlearning CVPR 2026 Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry AAAI 2026 Super Level Sets and Exponential Decay: A Synergistic Approach to Stable Neural Network Training (Abstract Reprint) AAAI 2026 The Convergence Behavior of Adam under Heavy-Tailed Noise UAI 2026 AdaGrad under Anisotropic Smoothness ICLR 2025 Adaptive Gradient Clipping for Robust Federated Learning ICLR 2025 Algorithms for ridge estimation with convergence guarantees JMLR 2025 A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models ICML 2025 A Pontryagin Perspective on Reinforcement Learning L4DC 2025 Approximate Global Convergence of Independent Learning in Multi-Agent Systems AISTATS 2025 A Stochastic Approach to the Subset Selection Problem via Mirror Descent ICLR 2025 AxlePro: Momentum-Accelerated Batched Training of Kernel Machines AISTATS 2025 Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning ICML 2025 Controlling Participation in Federated Learning with Feedback L4DC 2025 Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance ICML 2025 FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data IJCAI 2025