Yu-Guan Hsieh

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 24

Top Topics

Multi Armed Bandits

Adaptive Learning

Sampling Strategies

Top Venues

Publications

Yu-Guan Hsieh, Cheng-Yu Hsieh, Shih-Ying Yeh, Louis Béthune, Hadipour Ansari, Pavan Kumar Anasosalu Vasu, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Marco Cuturi
Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions. CoRR (2024)
Shih-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao, Bernard B. W. Yang, Giyeong Oh, Yanmin Gong
Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation. ICLR (2024)
Yu-Guan Hsieh, James Thornton, Eugène Ndiaye, Michal Klein, Marco Cuturi, Pierre Ablin
Careful with that Scalpel: Improving Gradient Surgery with an EMA. CoRR (2024)
Shin-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao, Bernard B. W. Yang, Giyeong Oh, Yanmin Gong
Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation. CoRR (2023)
Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick
Push-Pull With Device Sampling. IEEE Trans. Autom. Control. 68 (12) (2023)
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum
Thompson Sampling with Diffusion Generative Prior. CoRR (2023)
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum
Thompson Sampling with Diffusion Generative Prior. ICML (2023)
Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos
No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity via Learning Rate Separation. CoRR (2022)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism. J. Mach. Learn. Res. 23 (2022)
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton
Uplifting Bandits. CoRR (2022)
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton
Uplifting Bandits. NeurIPS (2022)
Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos
No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation. NeurIPS (2022)
Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick
Push-Pull with Device Sampling. CoRR (2022)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Optimization in Open Networks via Dual Averaging. CDC (2021)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Optimization in Open Networks via Dual Averaging. CoRR (2021)
Yu-Guan Hsieh, Kimon Antonakopoulos, Panayotis Mertikopoulos
Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium. CoRR (2021)
Yu-Guan Hsieh, Kimon Antonakopoulos, Panayotis Mertikopoulos
Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium. COLT (2021)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism. CoRR (2020)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling. CoRR (2020)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling. NeurIPS (2020)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
On the convergence of single-call stochastic extra-gradient methods. NeurIPS (2019)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
On the convergence of single-call stochastic extra-gradient methods. CoRR (2019)
Yu-Guan Hsieh, Gang Niu, Masashi Sugiyama
Classification from Positive, Unlabeled and Biased Negative Data. ICML (2019)
Yu-Guan Hsieh, Gang Niu, Masashi Sugiyama
Classification from Positive, Unlabeled and Biased Negative Data. CoRR (2018)