Yu-Guan Hsieh
11 papers · 2019–2025 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (29) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge · Bronze
🧬
Topic Evolution
🧭
Keyword Pioneer
🔥
Unstoppable · Bronze
🗃️
Keyword Collector
(59)
💎
Century Club · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(10)
Mathematics & Optimization
(6)
Learning Types · Machine Learning
(6)
Optimization
(6)
Optimization & Theory · Machine Learning
(6)
Artificial Intelligence
(4)
Deep Learning
(4)
Core AI
(3)
Models
(3)
Application Areas
(2)
Techniques
(2)
Core Methods
(1)
Learning Paradigms
(1)
Learning Types · Deep Learning
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
regret bound
(3)
stochastic optimization
(2)
convergence rate
(2)
diffusion model
(2)
no-regret learning
(2)
variationally stable game
(2)
game theory
(1)
binary classification
(1)
stochastic gradient
(1)
orthogonal projection
(1)
text-to-image generation
(1)
flow matching
(1)
posterior sampling
(1)
online decision making
(1)
model evaluation
(1)
online learning
(1)
mirror descent
(1)
nash equilibrium
(1)
prior distribution
(1)
weakly supervised learning
(1)
Papers
Simple ReFlow: Improved Techniques for Fast Flow Models
ICLR 2025
Careful with that Scalpel: Improving Gradient Surgery with an EMA
ICML 2024
Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation
ICLR 2024
Thompson Sampling with Diffusion Generative Prior
ICML 2023
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism
JMLR 2022
No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation
NeurIPS 2022
Uplifting Bandits
NeurIPS 2022
Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium
COLT 2021
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling
NeurIPS 2020
Classification from Positive, Unlabeled and Biased Negative Data
ICML 2019
On the convergence of single-call stochastic extra-gradient methods
NeurIPS 2019