10 papers
Gradient Methods with Online Scaling Part II. Practical Aspects
Ya-Chi Chu, Wenzhi Gao, Yinyu Ye +1
Part I of this work [Gao25] establishes online scaled gradient methods (OSGM), a framework that utilizes online convex optimization to adapt stepsizes in gradient methods. This pap…
Real-Time Reconstruction of 3D Bone Models via Very-Low-Dose Protocols
Yiqun Lin, Haoran Sun, Yongqing Li +12
Patient-specific bone models are essential for designing surgical guides and preoperative planning, as they enable the visualization of intricate anatomical structures. However, tr…
Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities
Yuexin Su, Ziyi Yang, Peiyuan Huang +2
Bandits with knapsacks (BwK) constitute a fundamental model that combines aspects of stochastic integer programming with online learning. Classical algorithms for BwK with a time h…
Adaptive Inertial Method
Han Long, Bingsheng He, Yinyu Ye +1
In this paper, we introduce the Adaptive Inertial Method (AIM), a novel framework for accelerated first-order methods through a customizable inertial term. We provide a rigorous co…
Gradient Methods with Online Scaling Part I. Theoretical Foundations
Wenzhi Gao, Ya-Chi Chu, Yinyu Ye +1
This paper establishes the theoretical foundations of the online scaled gradient methods (OSGM), a framework that utilizes online learning to adapt stepsizes and provably accelerat…
Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
Ya-Chi Chu, Wenzhi Gao, Yinyu Ye +1
This paper investigates the convergence properties of the hypergradient descent method (HDM), a 25-year-old heuristic originally proposed for adaptive stepsize selection in stochas…