Tootfinder

Single-loop Projection-free and Projected Gradient-based Algorithms for Nonconvex-concave Saddle Point Problems with Bilevel Structure
Mohammad Mahdi Ahmadi, Erfan Yazdandoost Hamedani
https://arxiv.org/abs/2404.13021

Single-loop Projection-free and Projected Gradient-based Algorithms for Nonconvex-concave Saddle Point Problems with Bilevel Structure
In this paper, we explore a class of constrained saddle point problems with a bilevel structure, where the upper-level objective function is nonconvex-concave and smooth subject to a strongly convex lower-level objective function. This class of problems finds wide applicability in machine learning, including robust multi-task learning, adversarial learning, and robust meta-learning. While some studies have focused on simpler formulations, e.g., when the upper-level objective function is linear …

A Microscopic Perspective on Moir\'e Materials
Kevin P. Nuckolls, Ali Yazdani
https://arxiv.org/abs/2404.08044 https://arxiv.org/…

A Microscopic Perspective on Moiré Materials
Contemporary quantum materials research is guided by themes of topology and of electronic correlations. A confluence of these two themes is engineered in "moiré materials", an emerging class of highly tunable, strongly correlated two-dimensional (2D) materials designed by the rotational or lattice misalignment of atomically thin crystals. In moiré materials, dominant Coulomb interactions among electrons give rise to collective electronic phases, often with robust topological properties. Ident…

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
Pooria Ashrafian, Milad Yazdani, Moein Heidari, Dena Shahriari, Ilker Hacihaliloglu
https://arxiv.org/abs/2403.19880

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
High-quality, large-scale data is essential for robust deep learning models in medical applications, particularly ultrasound image analysis. Diffusion models facilitate high-fidelity medical image generation, reducing the costs associated with acquiring and annotating new images. This paper utilizes recent vision-language models to produce diverse and realistic synthetic echocardiography image data, preserving key features of the original images guided by textual and semantic label maps. Specif…

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
Pooria Ashrafian, Milad Yazdani, Moein Heidari, Dena Shahriari, Ilker Hacihaliloglu
https://arxiv.org/abs/2403.19880

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
High-quality, large-scale data is essential for robust deep learning models in medical applications, particularly ultrasound image analysis. Diffusion models facilitate high-fidelity medical image generation, reducing the costs associated with acquiring and annotating new images. This paper utilizes recent vision-language models to produce diverse and realistic synthetic echocardiography image data, preserving key features of the original images guided by textual and semantic label maps. Specif…