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ORCIDAndre Wibisono
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2020 – today
- 2024
[c26]Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao:
Extragradient Type Methods for Riemannian Variational Inequality Problems. AISTATS 2024: 2080-2088- [c25]Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson:
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm. COLT 2024: 4593-4635 - [c24]Andre Wibisono, Yihong Wu, Kaylee Yingxi Yang:
Optimal score estimation via empirical Bayes smoothing. COLT 2024: 4958-4991 - [i26]Jiaming Liang, Siddharth Mitra, Andre Wibisono:
On Independent Samples Along the Langevin Diffusion and the Unadjusted Langevin Algorithm. CoRR abs/2402.17067 (2024) - [i25]Jonas Katona, Xiuyuan Wang, Andre Wibisono:
A Symplectic Analysis of Alternating Mirror Descent. CoRR abs/2405.03472 (2024) - 2023
- [c23]Bo Yuan, Jiaojiao Fan, Jiaming Liang, Andre Wibisono, Yongxin Chen:
On a Class of Gibbs Sampling over Networks. COLT 2023: 5754-5780 - [c22]Jun-Kun Wang, Andre Wibisono:
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization. ICLR 2023 - [c21]Jun-Kun Wang, Andre Wibisono:
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation. ICLR 2023 - [c20]Jun-Kun Wang, Andre Wibisono:
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time. ICLR 2023 - [c19]Jane H. Lee, Andre Wibisono, Emmanouil Zampetakis:
Learning Exponential Families from Truncated Samples. NeurIPS 2023 - [i24]Jun-Kun Wang, Andre Wibisono:
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization. CoRR abs/2302.07851 (2023) - [i23]Ketaki Joshi, Raghavendra Pradyumna Pothukuchi, Andre Wibisono, Abhishek Bhattacharjee:
Mitigating Catastrophic Forgetting in Long Short-Term Memory Networks. CoRR abs/2305.17244 (2023) - [i22]Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao:
Extragradient Type Methods for Riemannian Variational Inequality Problems. CoRR abs/2309.14155 (2023) - [i21]Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson:
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin Algorithm. CoRR abs/2312.08823 (2023) - 2022
- [c18]Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono:
The Mirror Langevin Algorithm Converges with Vanishing Bias. ALT 2022: 718-742 - [c17]Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono:
Improved analysis for a proximal algorithm for sampling. COLT 2022: 2984-3014 - [c16]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: 22839-22864 - [c15]Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker:
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings. MILCOM 2022: 470-477 - [c14]Andre Wibisono, Molei Tao, Georgios Piliouras:
Alternating Mirror Descent for Constrained Min-Max Games. NeurIPS 2022 - [i20]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 abs/2201.12488 (2022) - [i19]Andre Wibisono, Molei Tao, Georgios Piliouras:
Alternating Mirror Descent for Constrained Min-Max Games. CoRR abs/2206.04160 (2022) - [i18]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 abs/2206.11872 (2022) - [i17]Jun-Kun Wang, Andre Wibisono:
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time. CoRR abs/2207.02189 (2022) - [i16]Jun-Kun Wang, Andre Wibisono:
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation. CoRR abs/2210.10019 (2022) - [i15]Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker:
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings. CoRR abs/2210.16181 (2022) - [i14]Andre Wibisono, Kaylee Yingxi Yang:
Convergence in KL Divergence of the Inexact Langevin Algorithm with Application to Score-based Generative Models. CoRR abs/2211.01512 (2022) - 2021
- [c13]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: 3-47 - [c12]Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono:
Fast Convergence of Fictitious Play for Diagonal Payoff Matrices. SODA 2021: 1387-1404 - [i13]Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono:
The Mirror Langevin Algorithm Converges with Vanishing Bias. CoRR abs/2109.12077 (2021)
2010 – 2019
- 2019
- [c11]Santosh S. Vempala, Andre Wibisono:
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices. NeurIPS 2019: 8092-8104 - [c10]Ashia C. Wilson, Lester Mackey, Andre Wibisono:
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions. NeurIPS 2019: 13533-13543 - [i12]Santosh S. Vempala, Andre Wibisono:
Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices. CoRR abs/1903.08568 (2019) - [i11]Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono:
Last-iterate convergence rates for min-max optimization. CoRR abs/1906.02027 (2019) - [i10]Andre Wibisono:
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry. CoRR abs/1911.01469 (2019) - [i9]Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono:
Fictitious Play: Convergence, Smoothness, and Optimism. CoRR abs/1911.08418 (2019) - 2018
- [c9]Andre Wibisono:
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem. COLT 2018: 2093-3027 - [c8]Andre Wibisono, Varun S. Jog:
Convexity of Mutual Information Along the Heat Flow. ISIT 2018: 1615-1619 - [c7]Andre Wibisono, Varun S. Jog:
Convexity of mutual information along the Ornstein-Uhlenbeck flow. ISITA 2018: 55-59 - [i8]Andre Wibisono, Varun S. Jog:
Convexity of mutual information along the heat flow. CoRR abs/1801.06968 (2018) - [i7]Andre Wibisono:
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem. CoRR abs/1802.08089 (2018) - [i6]Andre Wibisono, Varun S. Jog:
Convexity of mutual information along the Ornstein-Uhlenbeck flow. CoRR abs/1805.01401 (2018) - 2017
- [c6]Andre Wibisono, Varun S. Jog, Po-Ling Loh:
Information and estimation in Fokker-Planck channels. ISIT 2017: 2673-2677 - [i5]Andre Wibisono, Varun S. Jog, Po-Ling Loh:
Information and estimation in Fokker-Planck channels. CoRR abs/1702.03656 (2017) - 2016
- [b1]Andre Wibisono:
Variational and Dynamical Perspectives On Learning and Optimization. University of California, Berkeley, USA, 2016 - [i4]Andre Wibisono, Ashia C. Wilson, Michael I. Jordan:
A Variational Perspective on Accelerated Methods in Optimization. CoRR abs/1603.04245 (2016) - 2015
- [j1]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): 2788-2806 (2015) - 2014
- [c5]Po-Ling Loh, Andre Wibisono:
Concavity of reweighted Kikuchi approximation. NIPS 2014: 3473-3481 - 2013
- [c4]Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan:
Streaming Variational Bayes. NIPS 2013: 1727-1735 - [c3]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: 2346-2354 - [i3]Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan:
Streaming Variational Bayes. CoRR abs/1307.6769 (2013) - [i2]John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono:
Optimal rates for zero-order optimization: the power of two function evaluations. CoRR abs/1312.2139 (2013) - 2012
- [c2]John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono:
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods. NIPS 2012: 1448-1456 - [c1]Jacob D. Abernethy, Rafael M. Frongillo, Andre Wibisono:
Minimax option pricing meets black-scholes in the limit. STOC 2012: 1029-1040 - [i1]Jacob D. Abernethy, Rafael M. Frongillo, Andre Wibisono:
Minimax Option Pricing Meets Black-Scholes in the Limit. CoRR abs/1202.2585 (2012)
Coauthor Index
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last updated on 2024-10-01 21:37 CEST by the dblp team
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