Jun-Kun Wang
15 papers · 2014–2025 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+6 more ↓ Show less ↑
🗺️ Taxonomy Completionist (29) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🧬
Topic Evolution
🏆
Grand Slam
🚀
Conference Pioneer
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
🗃️
Keyword Collector
(78)
Top co-authors
Research topics
Machine Learning
(14)
Optimization & Theory · Machine Learning
(13)
Mathematics & Optimization
(10)
Optimization
(8)
Deep Learning
(4)
Mathematics
(3)
Optimization & Theory · Deep Learning
(3)
Bayesian & Probabilistic
(2)
Learning Types
(2)
Artificial Intelligence
(1)
Natural Language Processing
(1)
Application Areas
(1)
Applications
(1)
Core AI
(1)
Core Methods
(1)
Keywords
gradient descent
(4)
non-convex optimization
(4)
regret bound
(3)
convex optimization
(3)
neural network optimization
(3)
online learning
(2)
convergence analysis
(2)
frank-wolfe method
(2)
zero-sum game
(2)
saddle point
(2)
test-time adaptation
(1)
text generation
(1)
game theory
(1)
robust regression
(1)
learning theory
(1)
domain adaptation
(1)
sample efficiency
(1)
nash equilibrium
(1)
time series prediction
(1)
binary classification
(1)
Papers
Online Detection of LLM-Generated Texts via Sequential Hypothesis Testing by Betting
ICML 2025
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time
ICLR 2023
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
ICLR 2023
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation
ICLR 2023
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out
ICML 2022
A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network
ICML 2021
An Optimistic Acceleration of AMSGrad for Nonconvex Optimization
ACML 2021
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron
ACML 2021
Escaping Saddle Points Faster with Stochastic Momentum
ICLR 2020
Online Linear Optimization with Sparsity Constraints
ALT 2019
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets
AAAI 2019
Acceleration through Optimistic No-Regret Dynamics
NeurIPS 2018
Faster Rates for Convex-Concave Games
COLT 2018
On Frank-Wolfe and Equilibrium Computation
NeurIPS 2017
Robust Inverse Covariance Estimation under Noisy Measurements
ICML 2014