Yu-Jie Zhang
17 papers · 2020–2025 · 5 venues · across top CS/AI venues
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Venues
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Research topics
Machine Learning
(16)
Learning Types
(12)
Optimization & Theory
(11)
Mathematics & Optimization
(8)
Optimization
(8)
Artificial Intelligence
(6)
Core Methods
(5)
Application Areas
(4)
Learning Paradigms
(4)
Reinforcement Learning
(2)
Core AI
(2)
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Computer Vision
(1)
Deep Learning
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Analysis
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Keywords
dynamic regret
(8)
online learning
(4)
online convex optimization
(3)
unbiased risk estimator
(3)
regret bound
(3)
domain adaptation
(2)
gradient variation
(2)
online mirror descent
(2)
non-stationary environment
(2)
stochastic optimization
(2)
distribution shift
(2)
policy learning
(1)
imitation learning
(1)
feature disentanglement
(1)
supervised learning
(1)
preference learning
(1)
reinforcement learning
(1)
function approximation
(1)
covariate shift
(1)
convex optimization
(1)
Papers
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
ICML 2025
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
ICML 2025
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization
JMLR 2024
Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation
ICML 2024
Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization
NeurIPS 2024
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical
ICML 2024
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
JMLR 2024
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation
NeurIPS 2024
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation
NeurIPS 2023
Imitation Learning from Vague Feedback
NeurIPS 2023
Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost
NeurIPS 2023
Adapting to Online Label Shift with Provable Guarantees
NeurIPS 2022
Exploratory Machine Learning with Unknown Unknowns
AAAI 2021
Towards Enabling Learnware to Handle Unseen Jobs
AAAI 2021
An Unbiased Risk Estimator for Learning with Augmented Classes
NeurIPS 2020
A Simple Online Algorithm for Competing with Dynamic Comparators
UAI 2020
Dynamic Regret of Convex and Smooth Functions
NeurIPS 2020