Showing 1–20 of 37 results
/ Date/ Name
Jun 2, 2022Self-Consistency of the Fokker-Planck EquationNov 13, 2016Accelerated Variance Reduced Block Coordinate DescentFeb 11, 2023Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEsSep 27, 2025Landing with the Score: Riemannian Optimization through DenoisingNov 9, 2020Sinkhorn Natural Gradient for Generative ModelsJul 20, 2020Sinkhorn Barycenter via Functional Gradient DescentMar 11, 2021Federated Functional Gradient BoostingJul 31, 2025Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion ModelsMar 24, 2026Manifold Generalization Provably Proceeds Memorization in Diffusion ModelsFeb 19, 2019Stochastic Conditional Gradient++Dec 31, 2024Poincare Inequality for Local Log-Polyak-Łojasiewicz Measures: Non-asymptotic Analysis in Low-temperature RegimeApr 23, 2023Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk MinimizationMay 25, 2018Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse CommunicationMar 4, 2019A Stochastic Trust Region Method for Non-convex MinimizationSep 29, 2025When Scores Learn Geometry: Rate Separations under the Manifold HypothesisJun 23, 2020Safe Learning under Uncertain Objectives and ConstraintsJul 14, 2024Learning to Steer Markovian Agents under Model UncertaintyNov 27, 2025Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-TuningOct 31, 2019A Decentralized Proximal Point-type Method for Saddle Point ProblemsOct 21, 2019Aggregated Gradient Langevin Dynamics