Andre Wibisono

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 44

Top Topics

Rapid Convergence

Machine Learning

Empirical Bayes

Top Venues

Publications

Jonas Katona, Xiuyuan Wang, Andre Wibisono
A Symplectic Analysis of Alternating Mirror Descent. CoRR (2024)
Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm. COLT (2024)
Andre Wibisono, Yihong Wu, Kaylee Yingxi Yang
Optimal score estimation via empirical Bayes smoothing. COLT (2024)
Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao
Extragradient Type Methods for Riemannian Variational Inequality Problems. AISTATS (2024)
Jiaming Liang, Siddharth Mitra, Andre Wibisono
On Independent Samples Along the Langevin Diffusion and the Unadjusted Langevin Algorithm. CoRR (2024)
Jun-Kun Wang, Andre Wibisono
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time. ICLR (2023)
Jun-Kun Wang, Andre Wibisono
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization. CoRR (2023)
Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin Algorithm. CoRR (2023)
Bo Yuan, Jiaojiao Fan, Jiaming Liang, Andre Wibisono, Yongxin Chen
On a Class of Gibbs Sampling over Networks. COLT (2023)
Jane Lee, Andre Wibisono, Emmanouil Zampetakis
Learning Exponential Families from Truncated Samples. NeurIPS (2023)
Jun-Kun Wang, Andre Wibisono
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation. ICLR (2023)
Jun-Kun Wang, Andre Wibisono
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization. ICLR (2023)
Ketaki Joshi, Raghavendra Pradyumna Pothukuchi, Andre Wibisono, Abhishek Bhattacharjee
Mitigating Catastrophic Forgetting in Long Short-Term Memory Networks. CoRR (2023)
Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao
Extragradient Type Methods for Riemannian Variational Inequality Problems. CoRR (2023)
Andre Wibisono, Kaylee Yingxi Yang
Convergence in KL Divergence of the Inexact Langevin Algorithm with Application to Score-based Generative Models. CoRR (2022)
Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings. MILCOM (2022)
Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono
Improved analysis for a proximal algorithm for sampling. COLT (2022)
Jun-Kun Wang, Andre Wibisono
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation. CoRR (2022)
Haizhou Du, Ryan Yang, Yijian Chen, Qiao Xiang, Andre Wibisono, Wei Huang
Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions. CoRR (2022)
Andre Wibisono, Molei Tao, Georgios Piliouras
Alternating Mirror Descent for Constrained Min-Max Games. CoRR (2022)
Andre Wibisono, Molei Tao, Georgios Piliouras
Alternating Mirror Descent for Constrained Min-Max Games. NeurIPS (2022)
Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out. CoRR (2022)
Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
The Mirror Langevin Algorithm Converges with Vanishing Bias. ALT (2022)
Jun-Kun Wang, Andre Wibisono
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time. CoRR (2022)
Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out. ICML (2022)
Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings. CoRR (2022)
Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
The Mirror Langevin Algorithm Converges with Vanishing Bias. CoRR (2021)
Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization. ALT (2021)
Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
Fast Convergence of Fictitious Play for Diagonal Payoff Matrices. SODA (2021)
Santosh S. Vempala, Andre Wibisono
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices. NeurIPS (2019)
Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
Fictitious Play: Convergence, Smoothness, and Optimism. CoRR (2019)
Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
Last-iterate convergence rates for min-max optimization. CoRR (2019)
Santosh S. Vempala, Andre Wibisono
Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices. CoRR (2019)
Ashia C. Wilson, Lester Mackey, Andre Wibisono
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions. NeurIPS (2019)
Andre Wibisono
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry. CoRR (2019)
Andre Wibisono, Varun S. Jog
Convexity of mutual information along the heat flow. CoRR (2018)
Andre Wibisono
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem. COLT (2018)
Andre Wibisono, Varun S. Jog
Convexity of Mutual Information Along the Heat Flow. ISIT (2018)
Andre Wibisono, Varun S. Jog
Convexity of mutual information along the Ornstein-Uhlenbeck flow. CoRR (2018)
Andre Wibisono
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem. CoRR (2018)
Andre Wibisono, Varun S. Jog
Convexity of mutual information along the Ornstein-Uhlenbeck flow. ISITA (2018)
Andre Wibisono, Varun S. Jog, Po-Ling Loh
Information and estimation in Fokker-Planck channels. ISIT (2017)
Andre Wibisono, Varun S. Jog, Po-Ling Loh
Information and estimation in Fokker-Planck channels. CoRR (2017)
Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
A Variational Perspective on Accelerated Methods in Optimization. CoRR (2016)
John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono
Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations. IEEE Trans. Inf. Theory 61 (5) (2015)
Po-Ling Loh, Andre Wibisono
Concavity of reweighted Kikuchi approximation. NIPS (2014)
Jacob D. Abernethy, Peter L. Bartlett, Rafael M. Frongillo, Andre Wibisono
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal. NIPS (2013)
Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
Streaming Variational Bayes. CoRR (2013)
John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono
Optimal rates for zero-order optimization: the power of two function evaluations. CoRR (2013)
Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
Streaming Variational Bayes. NIPS (2013)
John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods. NIPS (2012)
Jacob D. Abernethy, Rafael M. Frongillo, Andre Wibisono
Minimax option pricing meets black-scholes in the limit. STOC (2012)
Jacob D. Abernethy, Rafael M. Frongillo, Andre Wibisono
Minimax Option Pricing Meets Black-Scholes in the Limit CoRR (2012)