Andre Wibisono

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyCorreu electrònic verificat a cs.berkeley.edu
Ashia C. WilsonAssistant Professor at MITCorreu electrònic verificat a mit.edu
Jacob AbernethyAssistant Professor, University of MichiganCorreu electrònic verificat a umich.edu
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityCorreu electrònic verificat a stanford.edu
Santosh S. VempalaGeorgia TechCorreu electrònic verificat a gatech.edu
Kaylee Y. YangPhD student in Statistics and Data Science, Yale UniversityCorreu electrònic verificat a yale.edu
Tamara BroderickAssociate Professor of EECS, Massachusetts Institute of TechnologyCorreu electrònic verificat a mit.edu
Jun-Kun WangAssistant Professor at University of California San DiegoCorreu electrònic verificat a ucsd.edu
Molei TaoAssociate Professor, Georgia Institute of TechnologyCorreu electrònic verificat a gatech.edu
Lorenzo RosascoMaLGa Machine Learning Genoa Center - Università degli Studi di GenovaCorreu electrònic verificat a unige.it
TOMASO POGGIOMcDermott Professor in Brain Sciences, MITCorreu electrònic verificat a ai.mit.edu
Varun JogUniversity of CambridgeCorreu electrònic verificat a cam.ac.uk
Rafael FrongilloComputer Science, CU BoulderCorreu electrònic verificat a colorado.edu
Sinho ChewiYale UniversityCorreu electrònic verificat a yale.edu
Lester MackeyMicrosoft ResearchCorreu electrònic verificat a microsoft.com
Po-Ling LohUniversity of CambridgeCorreu electrònic verificat a cam.ac.uk
Georgios PiliourasGoogle DeepMind, Singapore University of Technology and DesignCorreu electrònic verificat a google.com
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyCorreu electrònic verificat a cs.berkeley.edu

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Andre Wibisono

Assistant Professor at Yale University

Correu electrònic verificat a yale.edu - Pàgina d'inici

Machine learning optimization sampling game theory


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
A variational perspective on accelerated methods in optimization A Wibisono, AC Wilson, MI Jordan proceedings of the National Academy of Sciences 113 (47), E7351-E7358, 2016	582	2016
Optimal rates for zero-order convex optimization: The power of two function evaluations JC Duchi, MI Jordan, MJ Wainwright, A Wibisono IEEE Transactions on Information Theory 61 (5), 2788-2806, 2015	562	2015
Streaming variational bayes T Broderick, N Boyd, A Wibisono, AC Wilson, MI Jordan Advances in neural information processing systems 26, 2013	411	2013
Rapid convergence of the unadjusted langevin algorithm: Isoperimetry suffices S Vempala, A Wibisono Advances in neural information processing systems 32, 2019	304	2019
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem A Wibisono Conference on learning theory, 2093-3027, 2018	205	2018
Improved analysis for a proximal algorithm for sampling Y Chen, S Chewi, A Salim, A Wibisono Conference on Learning Theory, 2984-3014, 2022	68	2022
Accelerating rescaled gradient descent: Fast optimization of smooth functions AC Wilson, L Mackey, A Wibisono Advances in Neural Information Processing Systems 32, 2019	64	2019
Last-iterate convergence rates for min-max optimization J Abernethy, KA Lai, A Wibisono arXiv preprint arXiv:1906.02027, 2019	62	2019
Maximum entropy distributions on graphs C Hillar, A Wibisono arXiv preprint arXiv:1301.3321, 2013	62	2013
Proximal langevin algorithm: Rapid convergence under isoperimetry A Wibisono arXiv preprint arXiv:1911.01469, 2019	49	2019
Last-iterate convergence rates for min-max optimization: Convergence of hamiltonian gradient descent and consensus optimization J Abernethy, KA Lai, A Wibisono Algorithmic Learning Theory, 3-47, 2021	43	2021
The mirror Langevin algorithm converges with vanishing bias R Li, M Tao, SS Vempala, A Wibisono International Conference on Algorithmic Learning Theory, 718-742, 2022	41	2022
Finite sample convergence rates of zero-order stochastic optimization methods A Wibisono, MJ Wainwright, M Jordan, JC Duchi Advances in Neural Information Processing Systems 25, 2012	40	2012
On accelerated methods in optimization A Wibisono, AC Wilson arXiv preprint arXiv:1509.03616, 2015	33	2015
Minimax option pricing meets Black-Scholes in the limit J Abernethy, RM Frongillo, A Wibisono Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012	27	2012
Optimal score estimation via empirical Bayes smoothing A Wibisono, Y Wu, KY Yang Conference on Learning Theory, 2024	25	2024
Convergence of the Inexact Langevin Algorithm and Score-based Generative Models in KL Divergence K Yingxi Yang, A Wibisono arXiv e-prints, arXiv: 2211.01512, 2022	22*	2022
Provable acceleration of heavy ball beyond quadratics for a class of Polyak-Lojasiewicz functions when the non-convexity is averaged-out JK Wang, CH Lin, A Wibisono, B Hu International conference on machine learning, 22839-22864, 2022	21	2022
Alternating mirror descent for constrained min-max games A Wibisono, M Tao, G Piliouras Advances in Neural Information Processing Systems 35, 35201-35212, 2022	18	2022
Information and estimation in Fokker-Planck channels A Wibisono, V Jog, PL Loh 2017 IEEE International Symposium on Information Theory (ISIT), 2673-2677, 2017	17	2017

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