Jun-Kun Wang

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 30

Top Topics

Convex Functions

Noisy Measurements

Top Venues

Publications

Jun-Kun Wang, Jacob D. Abernethy, Kfir Y. Levy
No-regret dynamics in the Fenchel game: a unified framework for algorithmic convex optimization. Math. Program. 205 (1) (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)
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)
Jun-Kun Wang, Andre Wibisono
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation. CoRR (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)
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)
Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy
A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network. ICML (2021)
Jun-Kun Wang, Jacob D. Abernethy
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron. ACML (2021)
Jun-Kun Wang, Xiaoyun Li, Belhal Karimi, Ping Li
An Optimistic Acceleration of AMSGrad for Nonconvex Optimization. ACML (2021)
Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy
Escaping Saddle Points Faster with Stochastic Momentum. CoRR (2021)
Jun-Kun Wang, Jacob D. Abernethy, Kfir Y. Levy
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization. CoRR (2021)
Jun-Kun Wang
Understanding Modern Techniques in Optimization: Frank-Wolfe, Nesterov's Momentum, and Polyak's Momentum. CoRR (2021)
Jun-Kun Wang, Jacob D. Abernethy
Quickly Finding a Benign Region via Heavy Ball Momentum in Non-Convex Optimization. CoRR (2020)
Jun-Kun Wang, Jacob D. Abernethy
Provable Acceleration of Neural Net Training via Polyak's Momentum. CoRR (2020)
Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy
Escaping Saddle Points Faster with Stochastic Momentum. ICLR (2020)
Jun-Kun Wang, Jacob D. Abernethy
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron. CoRR (2020)
Jun-Kun Wang, Xiaoyun Li, Ping Li
Optimistic Adaptive Acceleration for Optimization. CoRR (2019)
Jun-Kun Wang, Chi-Jen Lu, Shou-De Lin
Online Linear Optimization with Sparsity Constraints. ALT (2019)
Jarrid Rector-Brooks, Jun-Kun Wang, Barzan Mozafari
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets. AAAI (2019)
Jun-Kun Wang, Jacob D. Abernethy
Acceleration through Optimistic No-Regret Dynamics. NeurIPS (2018)
Jarrid Rector-Brooks, Jun-Kun Wang, Barzan Mozafari
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets. CoRR (2018)
Jun-Kun Wang, Jacob D. Abernethy
Acceleration through Optimistic No-Regret Dynamics. CoRR (2018)
Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang
Faster Rates for Convex-Concave Games. CoRR (2018)
Jacob D. Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang
Faster Rates for Convex-Concave Games. COLT (2018)
Jacob D. Abernethy, Jun-Kun Wang
On Frank-Wolfe and Equilibrium Computation. NIPS (2017)
Jun-Kun Wang, Shou-De Lin
Efficient Sampling-Based ADMM for Distributed Data. DSAA (2016)
Jun-Kun Wang, Shou-De Lin
Parallel Least-Squares Policy Iteration. DSAA (2016)
Jun-Kun Wang, Shou-de Lin
Robust Inverse Covariance Estimation under Noisy Measurements. ICML (2014)