1 citations · 1 across the 5 of their papers we have counts for
4 papers · 1 filter
Mathematics of Data Science
Afonso S. Bandeira, Amit Singer, Thomas Strohmer
This book is about the mathematical foundations of data science. 1. Introduction 2. Curses, Blessings, and Surprises in High Dimensions 3. Singular Value Decomposition and Principa…
Machine Unlearning via Information Theoretic Regularization
Shizhou Xu, Thomas Strohmer
How can we effectively remove or ``unlearn'' undesirable information, such as specific features or the influence of individual data points, from a learning outcome while minimizing…
Towards Multiscale Graph-based Protein Learning with Geometric Secondary Structural Motifs
Shih-Hsin Wang, Yuhao Huang, Taos Transue +4
Graph neural networks (GNNs) have emerged as powerful tools for learning protein structures by capturing spatial relationships at the residue level. However, existing GNN-based met…
FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration
Xue Feng, M. Paul Laiu, Thomas Strohmer
Federated learning (FL) is a distributed machine learning approach that enables multiple local clients and a central server to collaboratively train a model while keeping the data…