3 papers
cs.LG2025
Towards Robust Learning to Optimize with Theoretical Guarantees
Qingyu Song, Wei Lin, Juncheng Wang +1
Learning to optimize (L2O) is an emerging technique to solve mathematical optimization problems with learning-based methods. Although with great success in many real-world scenario…
cs.CV2024
Optimization-Driven Statistical Models of Anatomies using Radial Basis Function Shape Representation
Hong Xu, Shireen Y. Elhabian
Particle-based shape modeling (PSM) is a popular approach to automatically quantify shape variability in populations of anatomies. The PSM family of methods employs optimization to…
cs.CV2023
Particle-Based Shape Modeling for Arbitrary Regions-of-Interest
Hong Xu, Alan Morris, Shireen Y. Elhabian
Statistical Shape Modeling (SSM) is a quantitative method for analyzing morphological variations in anatomical structures. These analyses often necessitate building models on targe…