3 papers
eess.IV2026
Variable-Rate Deep Image Compression based on Low-Rank Adaptation by Progressive Learning
Xing-Yu Xu, Chen-Hsiu Huang, Ja-Ling Wu
In the digital age, image compression is crucial for numerous applications, including web media, streaming services, high-resolution medical imaging, and connected vehicle networks…
cs.LG2026
Provably Efficient and Agile Randomized Q-Learning
He Wang, Xingyu Xu, Yuejie Chi
While Bayesian-based exploration often demonstrates superior empirical performance compared to bonus-based methods in model-based reinforcement learning (RL), its theoretical under…
cs.LG2026
Polynomial Convergence of Riemannian Diffusion Models
Xingyu Xu, Ziyi Zhang, Yorie Nakahira +2
Diffusion models have demonstrated remarkable empirical success in the recent years and are considered one of the state-of-the-art generative models in modern AI. These models cons…