Hsieh, Yu-Guan

12 publications

ICLR 2025 Simple ReFlow: Improved Techniques for Fast Flow Models Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul Ye, Bahjat Kawar, James Thornton

ICML 2024 Careful with That Scalpel: Improving Gradient Surgery with an EMA Yu-Guan Hsieh, James Thornton, Eugene Ndiaye, Michal Klein, Marco Cuturi, Pierre Ablin

ICLR 2024 Navigating Text-to-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation Shih-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao, Bernard B W Yang, Giyeong Oh, Yanmin Gong

ICML 2023 Thompson Sampling with Diffusion Generative Prior Yu-Guan Hsieh, Shiva Kasiviswanathan, Branislav Kveton, Patrick Blöbaum

NeurIPSW 2022 Diffusion Prior for Online Decision Making: A Case Study of Thompson Sampling Yu-Guan Hsieh, Shiva Kasiviswanathan, Branislav Kveton, Patrick Blöbaum

JMLR 2022 Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

NeurIPS 2022 No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity via Learning Rate Separation Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos

NeurIPS 2022 Uplifting Bandits Yu-Guan Hsieh, Shiva P. Kasiviswanathan, Branislav Kveton

COLT 2021 Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium Yu-Guan Hsieh, Kimon Antonakopoulos, Panayotis Mertikopoulos

NeurIPS 2020 Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

ICML 2019 Classification from Positive, Unlabeled and Biased Negative Data Yu-Guan Hsieh, Gang Niu, Masashi Sugiyama

NeurIPS 2019 On the Convergence of Single-Call Stochastic Extra-Gradient Methods Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos