conftrace_

stochastic method

95 papers

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Co-occurring keywords

convex optimization (1321) regret bound (1926) online learning (1777) non-convex optimization (547) markov chain monte carlo (725) stochastic optimization (1060) convergence rate (607) gradient descent (1144) distributed optimization (275) stochastic gradient descent (1091)

Papers

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin ICCV 2025
Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology AAAI 2025
Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport AAAI 2025
Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity NIPS 2024
Universal Exact Compression of Differentially Private Mechanisms NIPS 2024
Mean-Field Langevin Dynamics for Signed Measures via a Bilevel Approach NIPS 2024
Gradient-free optimization of highly smooth functions: improved analysis and a new algorithm JMLR 2024
Efficient Combinatorial Optimization via Heat Diffusion NIPS 2024
Robust Reinforcement Learning with General Utility NIPS 2024
No Internal Regret with Non-convex Loss Functions AAAI 2024
Higher-Order Causal Message Passing for Experimentation with Complex Interference NIPS 2024
Towards Stability and Generalization Bounds in Decentralized Minibatch Stochastic Gradient Descent AAAI 2024
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization NIPS 2024
Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms NIPS 2024
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards NIPS 2023
Accelerated Stochastic Optimization Methods under Quasar-convexity ICML 2023
Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition JMLR 2023
A Guide Through the Zoo of Biased SGD NIPS 2023
On the Efficacy of Sampling Adapters ACL 2023
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability ICML 2023
Optimal Shrinkage for Distributed Second-Order Optimization ICML 2023
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation ICML 2023
PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods AISTATS 2023
Gibbsian Polar Slice Sampling ICML 2023