Yu-Guan Hsieh

According to our database, Yu-Guan Hsieh authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Simple ReFlow: Improved Techniques for Fast Flow Models.

Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul Ye, Bahjat Kawar, James Thornton

CoRR, 2024

Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions.

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

CoRR, 2024

Careful with that Scalpel: Improving Gradient Surgery with an EMA.

Yu-Guan Hsieh, James Thornton, Eugène Ndiaye, Michal Klein, Marco Cuturi, Pierre Ablin

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Push-Pull With Device Sampling.

Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick

IEEE Trans. Autom. Control., December, 2023

Decision-Making in multi-agent systems: delays, adaptivity, and learning in games. (Prise de décision dans les systèmes multi-agents: délais, adaptabilité et apprentissage dans les jeux).

Yu-Guan Hsieh

PhD thesis, 2023

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

Shin-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao, Bernard B. W. Yang, Giyeong Oh, Yanmin Gong

CoRR, 2023

Thompson Sampling with Diffusion Generative Prior.

Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum

Proceedings of the International Conference on Machine Learning, 2023

2022

Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

J. Mach. Learn. Res., 2022

Uplifting Bandits.

Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium.

Yu-Guan Hsieh, Kimon Antonakopoulos, Panayotis Mertikopoulos

Proceedings of the Conference on Learning Theory, 2021

Optimization in Open Networks via Dual Averaging.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

On the convergence of single-call stochastic extra-gradient methods.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Classification from Positive, Unlabeled and Biased Negative Data.

Yu-Guan Hsieh, Gang Niu, Masashi Sugiyama

Proceedings of the 36th International Conference on Machine Learning, 2019