TA6a5: Supervised and Self-supervised Learning
Tue, 31 Oct, 08:15 - 09:55 PT (UTC -8)
Location: Fred Farr
Session Type: Poster
Session Chair: Eliabelle Mauduit, ENSTA Paris
Track: Adaptive Systems, Machine Learning, Data Analytics

TA6a5.1: Constrained Hierarchical Clustering via Graph Coarsening and Optimal Cuts
Eliabelle Mauduit, Andrea Simonetto, ENSTA Paris, France

TA6a5.2: Enhancing Neural Network Performance for Problems in the Physical Sciences: Applications to Electromagnetic Signal Source Localization
Maria Barger, Worcester Polytechnic Institute, United States; Evan Witz, Wisconsin Lutheran College, United States; Randy Paffenroth, Worcester Polytechnic Institute, United States

TA6a5.3: A Novel Cardiac Arrhythmia Classification Method Using Visibility Graphs and Graph Convolutional Network
Dorsa EPMoghaddam, Ananya Muguli, Behnaam Aazhang, Rice University, United States

TA6a5.4: Knowledge Distillation by Compressive Sampling
Shreyas Chaudhari, Jose Moura, Carnegie Mellon University, United States