TA8b-2.5

Deep Linearization Mappings for Canonical Correlation Clustering

Akshay Malhotra, InterDigital Communications, United States; Ioannis Schizas, US Army Research Laboratory, United States; João Morais, Arizona State University, United States
Session:
TA8b-2: Information Processing with Networks and Graphs II Poster
Track:
Networks and Graphs
Location:
Poster - Kiln
Presentation Time:
Tue, 29 Oct, 10:15 - 11:55 PT (UTC -8)
Session Chair:
John Shi, Carnegie Mellon University
Presentation
Discussion
Resources
No resources available.
Session TA8b-2
TA8b-2.1: Cyberattack Aware Load Frequency Control in Power Systems
Shahriar Rahman Fahim, Texas A&M University, United States; Rachad Atat, Texas A&M University at Qatar, Qatar; Cihat Kececi, Texas A&M University, United States; Abdulrahman Takiddin, Florida State University, United States; Muhammad Ismail, Tennessee Tech University, United States; Katherine Davis, Erchin Serpedin, Texas A&M University, United States
TA8b-2.2: Binary Relaxation on Unlabeled Graph Matching: a Twin-VAMP Approach
Akrout Mohamed, Faouzi Bellili, Amine Mezghani, University of Manitoba, Canada
TA8b-2.3: Structure-Guided Input Graph for GNNs facing Heterophily
Victor M. Tenorio, King Juan Carlos University, Spain; Madeline Navarro, Rice University, United States; Samuel Rey, King Juan Carlos University, Spain; Santiago Segarra, Rice University, United States; Antonio G. Marques, King Juan Carlos University, Spain
TA8b-2.4: Form-Finding and Physical Property Predictions of Tensegrity Structures Using Deep Neural Networks
Muhao Chen, Jing Qin, University of Kentucky, United States
TA8b-2.5: Deep Linearization Mappings for Canonical Correlation Clustering
Akshay Malhotra, InterDigital Communications, United States; Ioannis Schizas, US Army Research Laboratory, United States; João Morais, Arizona State University, United States
Contacts