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Andre Wibisono

26 papers · 2012–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (13) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (8) 🌍 Conference Polyglot (6) 🌟 Keyword Trendsetter Combo (4) 🧬 Topic Evolution πŸ”₯ Unstoppable (5) πŸ’Ž Century Club (26) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (108) ⚑ Prolific Year (5)

Conferences

COLT (9) NIPS (8) ALT (4) ICLR (3) AISTATS (1) ICML (1)

Top co-authors

Jun-Kun Wang (4) Siddharth Mitra (3) Molei Tao (3) Michael I. Jordan (2) Yongxin Chen (2) Ashia Wilson (2) Ashia C Wilson (2) Vishwak Srinivasan (2) Georgios Piliouras (2) Jacob Abernethy (2)

Research topics

Statistics (1)

Keywords

convex optimization (4) markov chain monte carlo (3) convergence rate (3) gradient descent (2) log-concave distribution (2) langevin dynamics (2) stochastic process (2) mirror descent (2) last-iterate convergence (2) non-convex optimization (2) minimax optimization (1) topic modeling (1) kl divergence (1) constrained optimization (1) variational inference (1) stochastic gradient descent (1) parameter estimation (1) partition function (1) belief propagation (1) regret minimization (1)

Papers

Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality (Extended Abstract) COLT 2025
Fast Convergence of $Ξ¦$-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler ALT 2025
High-accuracy sampling from constrained spaces with the Metropolis-adjusted Preconditioned Langevin Algorithm ALT 2025
On the Convergence of Min-Max Langevin Dynamics and Algorithm COLT 2025
Fast and Furious Symmetric Learning in Zero-Sum Games: Gradient Descent as Fictitious Play COLT 2025
Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of $Ξ¦$-Mutual Information (Extended Abstract) COLT 2025
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm COLT 2024
Optimal score estimation via empirical Bayes smoothing COLT 2024
Extragradient Type Methods for Riemannian Variational Inequality Problems AISTATS 2024
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization ICLR 2023
Learning Exponential Families from Truncated Samples NIPS 2023
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation ICLR 2023
On a Class of Gibbs Sampling over Networks COLT 2023
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time ICLR 2023
Alternating Mirror Descent for Constrained Min-Max Games NIPS 2022
The Mirror Langevin Algorithm Converges with Vanishing Bias ALT 2022
Improved analysis for a proximal algorithm for sampling COLT 2022
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out ICML 2022
Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization ALT 2021
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices NIPS 2019
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions NIPS 2019
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem COLT 2018
Concavity of reweighted Kikuchi approximation NIPS 2014
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal NIPS 2013
Streaming Variational Bayes NIPS 2013
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NIPS 2012