Andre Wibisono

70 papers A* 19A 1B 6C 1Journal 37Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Symplectic Analysis of Alternating Mirror Descent. J. Mach. Learn. Res. Jonas E. Katona, Xiuyuan Wang, Andre Wibisono
2026	J	`jnl`	Characterizing Dependence of Samples Along the Langevin Dynamics and Algorithms via Contraction of Φ-Mutual Information. IEEE Trans. Inf. Theory Jiaming Liang, Siddharth Mitra, Andre Wibisono
2026	J	`jnl`	Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality. IEEE Trans. Inf. Theory Andre Wibisono
2026	J	`jnl`	Tail-Sensitive KL and Rényi Convergence of Unadjusted Hamiltonian Monte Carlo via One-Shot Couplings. CoRR Nawaf Bou-Rabee, Siddharth Mitra, Andre Wibisono
2026	J	`jnl`	The Geometry of Efficient Nonconvex Sampling. CoRR Santosh S. Vempala, Andre Wibisono
2025	A*	`conf`	Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of Φ-Mutual Information (Extended Abstract). COLT Jiaming Liang, Siddharth Mitra, Andre Wibisono
2025	B	`conf`	Fast Convergence of Φ-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler. ALT Siddharth Mitra, Andre Wibisono
2025	A*	`conf`	Fast and Furious Symmetric Learning in Zero-Sum Games: Gradient Descent as Fictitious Play. COLT John Lazarsfeld, Georgios Piliouras, Ryann Sim, Andre Wibisono
2025	J	`jnl`	Fast and Furious Symmetric Learning in Zero-Sum Games: Gradient Descent as Fictitious Play. CoRR John Lazarsfeld, Georgios Piliouras, Ryann Sim, Andre Wibisono
2025	J	`jnl`	Hamiltonian Descent Algorithms for Optimization: Accelerated Rates via Randomized Integration Time. CoRR Qiang Fu, Andre Wibisono
2025	B	`conf`	High-accuracy sampling from constrained spaces with the Metropolis-adjusted Preconditioned Langevin Algorithm. ALT Vishwak Srinivasan, Andre Wibisono, Ashia Wilson
2025	A*	`conf`	Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality (Extended Abstract). COLT Andre Wibisono
2025	J	`jnl`	Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality. CoRR Andre Wibisono
2025	A*	`conf`	On the Convergence of Min-Max Langevin Dynamics and Algorithm. COLT Yang Cai, Siddharth Mitra, Xiuyuan Wang, Andre Wibisono
2024	J	`jnl`	A Symplectic Analysis of Alternating Mirror Descent. CoRR Jonas E. Katona, Xiuyuan Wang, Andre Wibisono
2024	J	`jnl`	Convergence of the Min-Max Langevin Dynamics and Algorithm for Zero-Sum Games. CoRR Yang Cai, Siddharth Mitra, Xiuyuan Wang, Andre Wibisono
2024	A	`conf`	Extragradient Type Methods for Riemannian Variational Inequality Problems. AISTATS Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao
2024	J	`jnl`	Fast Convergence of Ψ-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler. CoRR Siddharth Mitra, Andre Wibisono
2024	A*	`conf`	Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm. COLT Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson
2024	J	`jnl`	On Independent Samples Along the Langevin Diffusion and the Unadjusted Langevin Algorithm. CoRR Jiaming Liang, Siddharth Mitra, Andre Wibisono
2024	A*	`conf`	Optimal score estimation via empirical Bayes smoothing. COLT Andre Wibisono, Yihong Wu, Kaylee Yingxi Yang
2023	A*	`conf`	Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time. ICLR Jun-Kun Wang, Andre Wibisono
2023	A*	`conf`	Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization. ICLR Jun-Kun Wang, Andre Wibisono
2023	J	`jnl`	Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization. CoRR Jun-Kun Wang, Andre Wibisono
2023	J	`jnl`	Extragradient Type Methods for Riemannian Variational Inequality Problems. CoRR Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao
2023	J	`jnl`	Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin Algorithm. CoRR Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson
2023	A*	`conf`	Learning Exponential Families from Truncated Samples. NeurIPS Jane H. Lee, Andre Wibisono, Emmanouil Zampetakis
2023	J	`jnl`	Mitigating Catastrophic Forgetting in Long Short-Term Memory Networks. CoRR Ketaki Joshi, Raghavendra Pradyumna Pothukuchi, Andre Wibisono, Abhishek Bhattacharjee
2023	A*	`conf`	On a Class of Gibbs Sampling over Networks. COLT Bo Yuan, Jiaojiao Fan, Jiaming Liang, Andre Wibisono, Yongxin Chen
2023	A*	`conf`	Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation. ICLR Jun-Kun Wang, Andre Wibisono
2022	J	`jnl`	Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time. CoRR Jun-Kun Wang, Andre Wibisono
2022	J	`jnl`	Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions. CoRR Haizhou Du, Ryan Yang, Yijian Chen, Qiao Xiang, Andre Wibisono, Wei Huang
2022	—	`conf`	Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings. MILCOM Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker
2022	J	`jnl`	Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings. CoRR Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker
2022	A*	`conf`	Alternating Mirror Descent for Constrained Min-Max Games. NeurIPS Andre Wibisono, Molei Tao, Georgios Piliouras
2022	J	`jnl`	Alternating Mirror Descent for Constrained Min-Max Games. CoRR Andre Wibisono, Molei Tao, Georgios Piliouras
2022	J	`jnl`	Convergence in KL Divergence of the Inexact Langevin Algorithm with Application to Score-based Generative Models. CoRR Andre Wibisono, Kaylee Yingxi Yang
2022	A*	`conf`	Improved analysis for a proximal algorithm for sampling. COLT Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono
2022	A*	`conf`	Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out. ICML Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu
2022	J	`jnl`	Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out. CoRR Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu
2022	B	`conf`	The Mirror Langevin Algorithm Converges with Vanishing Bias. ALT Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
2022	J	`jnl`	Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation. CoRR Jun-Kun Wang, Andre Wibisono
2021	A*	`conf`	Fast Convergence of Fictitious Play for Diagonal Payoff Matrices. SODA Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
2021	B	`conf`	Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization. ALT Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
2021	J	`jnl`	The Mirror Langevin Algorithm Converges with Vanishing Bias. CoRR Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
2019	A*	`conf`	Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions. NeurIPS Ashia C. Wilson, Lester Mackey, Andre Wibisono
2019	J	`jnl`	Fictitious Play: Convergence, Smoothness, and Optimism. CoRR Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
2019	J	`jnl`	Last-iterate convergence rates for min-max optimization. CoRR Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono
2019	J	`jnl`	Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry. CoRR Andre Wibisono
2019	A*	`conf`	Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices. NeurIPS Santosh S. Vempala, Andre Wibisono
2019	J	`jnl`	Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices. CoRR Santosh S. Vempala, Andre Wibisono
2018	B	`conf`	Convexity of Mutual Information Along the Heat Flow. ISIT Andre Wibisono, Varun S. Jog
2018	C	`conf`	Convexity of mutual information along the Ornstein-Uhlenbeck flow. ISITA Andre Wibisono, Varun S. Jog
2018	J	`jnl`	Convexity of mutual information along the Ornstein-Uhlenbeck flow. CoRR Andre Wibisono, Varun S. Jog
2018	J	`jnl`	Convexity of mutual information along the heat flow. CoRR Andre Wibisono, Varun S. Jog
2018	A*	`conf`	Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem. COLT Andre Wibisono
2018	J	`jnl`	Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem. CoRR Andre Wibisono
2017	B	`conf`	Information and estimation in Fokker-Planck channels. ISIT Andre Wibisono, Varun S. Jog, Po-Ling Loh
2017	J	`jnl`	Information and estimation in Fokker-Planck channels. CoRR Andre Wibisono, Varun S. Jog, Po-Ling Loh
2016	J	`jnl`	A Variational Perspective on Accelerated Methods in Optimization. CoRR Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
2016	—	`—`	Variational and Dynamical Perspectives On Learning and Optimization. Andre Wibisono
2015	J	`jnl`	Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations. IEEE Trans. Inf. Theory John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono
2014	—	`conf`	Concavity of reweighted Kikuchi approximation. NIPS Po-Ling Loh, Andre Wibisono
2013	—	`conf`	How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal. NIPS Jacob D. Abernethy, Peter L. Bartlett, Rafael M. Frongillo, Andre Wibisono
2013	J	`jnl`	Optimal rates for zero-order optimization: the power of two function evaluations. CoRR John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono
2013	—	`conf`	Streaming Variational Bayes. NIPS Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
2013	J	`jnl`	Streaming Variational Bayes. CoRR Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
2012	—	`conf`	Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods. NIPS John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono
2012	J	`jnl`	Minimax Option Pricing Meets Black-Scholes in the Limit CoRR Jacob D. Abernethy, Rafael M. Frongillo, Andre Wibisono
2012	A*	`conf`	Minimax option pricing meets black-scholes in the limit. STOC Jacob D. Abernethy, Rafael M. Frongillo, Andre Wibisono