Jun-Kun Wang

36 papers A* 11B 3C 2Journal 18Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Frictionless Hamiltonian Descent with Discretization and Parallel Optimization.
Trans. Mach. Learn. Res.
Heng Zhu, Jun-Kun Wang
2025 A* conf
Online Detection of LLM-Generated Texts via Sequential Hypothesis Testing by Betting.
ICML
Can Chen, Jun-Kun Wang
2025 J jnl
Optimistic Interior Point Methods for Sequential Hypothesis Testing by Betting.
CoRR
Can Chen, Jun-Kun Wang
2024 J jnl
No-regret dynamics in the Fenchel game: a unified framework for algorithmic convex optimization.
Math. Program.
Jun-Kun Wang, Jacob D. Abernethy, Kfir Y. Levy
2024 J jnl
Online Detecting LLM-Generated Texts via Sequential Hypothesis Testing by Betting.
CoRR
Can Chen, Jun-Kun Wang
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 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 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 J jnl
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation.
CoRR
Jun-Kun Wang, Andre Wibisono
2021 A* conf
A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network.
ICML
Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy
2021 C conf
An Optimistic Acceleration of AMSGrad for Nonconvex Optimization.
ACML
Jun-Kun Wang, Xiaoyun Li, Belhal Karimi, Ping Li
2021 J jnl
Escaping Saddle Points Faster with Stochastic Momentum.
CoRR
Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy
2021 J jnl
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization.
CoRR
Jun-Kun Wang, Jacob D. Abernethy, Kfir Y. Levy
2021 C conf
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron.
ACML
Jun-Kun Wang, Jacob D. Abernethy
2021 J jnl
Understanding Modern Techniques in Optimization: Frank-Wolfe, Nesterov's Momentum, and Polyak's Momentum.
CoRR
Jun-Kun Wang
2021 — —
Understanding Modern Techniques in Optimization: Frank-Wolfe, Nesterov's Momentum, and Polyak's Momentum.
Jun-Kun Wang
2020 A* conf
Escaping Saddle Points Faster with Stochastic Momentum.
ICLR
Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy
2020 J jnl
Provable Acceleration of Neural Net Training via Polyak's Momentum.
CoRR
Jun-Kun Wang, Jacob D. Abernethy
2020 J jnl
Quickly Finding a Benign Region via Heavy Ball Momentum in Non-Convex Optimization.
CoRR
Jun-Kun Wang, Jacob D. Abernethy
2020 J jnl
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron.
CoRR
Jun-Kun Wang, Jacob D. Abernethy
2019 B conf
Online Linear Optimization with Sparsity Constraints.
ALT
Jun-Kun Wang, Chi-Jen Lu, Shou-De Lin
2019 J jnl
Optimistic Adaptive Acceleration for Optimization.
CoRR
Jun-Kun Wang, Xiaoyun Li, Ping Li
2019 A* conf
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets.
AAAI
Jarrid Rector-Brooks, Jun-Kun Wang, Barzan Mozafari
2018 A* conf
Acceleration through Optimistic No-Regret Dynamics.
NeurIPS
Jun-Kun Wang, Jacob D. Abernethy
2018 J jnl
Acceleration through Optimistic No-Regret Dynamics.
CoRR
Jun-Kun Wang, Jacob D. Abernethy
2018 A* conf
Faster Rates for Convex-Concave Games.
COLT
Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang
2018 J jnl
Faster Rates for Convex-Concave Games.
CoRR
Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang
2018 J jnl
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets.
CoRR
Jarrid Rector-Brooks, Jun-Kun Wang, Barzan Mozafari
2017 — conf
On Frank-Wolfe and Equilibrium Computation.
NIPS
Jacob D. Abernethy, Jun-Kun Wang
2016 B conf
Efficient Sampling-Based ADMM for Distributed Data.
DSAA
Jun-Kun Wang, Shou-De Lin
2016 B conf
Parallel Least-Squares Policy Iteration.
DSAA
Jun-Kun Wang, Shou-De Lin
2014 A* conf
Robust Inverse Covariance Estimation under Noisy Measurements.
ICML
Jun-Kun Wang, Shou-De Lin