61 citations · 358 across the 40 of their papers we have counts for
4 papers · 1 filter
Dimensionality reduction, regularization, and generalization in overparameterized regressions
Ningyuan Huang, David W. Hogg, Soledad Villar
Overparameterization in deep learning is powerful: Very large models fit the training data perfectly and yet often generalize well. This realization brought back the study of linea…
Seabed classification using physics-based modeling and machine learning
Christina Frederick, Soledad Villar, Zoi-Heleni Michalopoulou
In this work model-based methods are employed along with machine learning techniques to classify sediments in oceanic environments based on the geoacoustic properties of a two-laye…
MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data
Andrew J. Blumberg, Mathieu Carriere, Michael A. Mandell +2
Comparing and aligning large datasets is a pervasive problem occurring across many different knowledge domains. We introduce and study MREC, a recursive decomposition algorithm for…
Can Graph Neural Networks Count Substructures?
Zhengdao Chen, Lei Chen, Soledad Villar +1
The ability to detect and count certain substructures in graphs is important for solving many tasks on graph-structured data, especially in the contexts of computational chemistry…