Yu-Guan Hsieh

11 papers · 2019–2025 · 5 conferences · across top CS/AI conferences

Achievements

🗺️ Taxonomy Completionist (21) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🏃 Academic Marathon (6) 💎 Century Club (11) 🔥 Unstoppable (7)

Conferences

NIPS (4) ICML (3) ICLR (2) COLT (1) JMLR (1)

Top co-authors

Panayotis Mertikopoulos (5) Jérôme Malick (3) Franck Iutzeler (3) Kimon Antonakopoulos (2) Branislav Kveton (2) James Thornton (2) Marco Cuturi (2) Michal Klein (2) Zhidong Gao (1) Eugene Ndiaye (1)

Keywords

no-regret learning (2) regret bound (2) convergence rate (2) stochastic optimization (2) variationally stable game (2) game theory (1) binary classification (1) stochastic gradient (1) online decision making (1) posterior sampling (1) positive unlabeled learning (1) empirical risk minimization (1) regret minimization (1) nash equilibrium (1) online learning (1) thompson sampling (1) ucb algorithm (1) weakly supervised learning (1) asynchronous optimization (1) optimization theory (1)

Papers

Simple ReFlow: Improved Techniques for Fast Flow Models ICLR 2025

Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation ICLR 2024

Careful with that Scalpel: Improving Gradient Surgery with an EMA ICML 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 NIPS 2022

Uplifting Bandits NIPS 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 NIPS 2020

Classification from Positive, Unlabeled and Biased Negative Data ICML 2019

On the convergence of single-call stochastic extra-gradient methods NIPS 2019