TA8b-1: Information Processing with Networks and Graphs I
Tue, 29 Oct, 10:15 - 11:55 PT (UTC -7)
Location: Poster - Fred Farr
Session Type: Poster
Track: Networks and Graphs

TA8b-1.1: Tight Local Graph Fourier Frames with Finite Support

Philipp Reingruber, Gerald Matz, TU Wien, Austria

TA8b-1.2: An Approach for Direct Tracking of Multiple Sources

Mingchao Liang, Florian Meyer, University of California, San Diego, United States

TA8b-1.3: Peer-to-Peer Deep Learning for Beyond-5G IoT

Srinivasa Pranav, José M.F. Moura, Carnegie Mellon University, United States

TA8b-1.4: Distributionally Robust Power Policies for Wireless Systems under Power Fluctuation Risk

Gokberk Yaylali, Dionysis Kalogerias, Yale University, United States

TA8b-1.5: Byzantine-resilient Collaborative Hierarchical Non-Bayesian Learning

Connor Mclaughlin, Northeastern University, United States; Matthew Ding, University of California, Berkeley, United States; Deniz Erdogmus, Lili Su, Northeastern University, United States

TA8b-1.6: The Sample Complexity of Differential Analysis for Networks that Obey Conservation Laws

Jiajun Cheng, Anirudh Rayas, Arizona State University, United States; Rajasekhar Anguluri, University of Maryland, Baltimore County, United States; Gautam Dasarathy, Arizona State University, United States

TA8b-1.7: Online Cache Optimization Without File Splitting

David Garrido, Universidad Carlos III of Madrid, Spain; Hashem Moradmand, IRIB, Iran; Borja Peleato, University Carlos III of Madrid, Spain

TA8b-1.8: Multiview Graph Learning Based on Node Perturbation Model

Mohammad Alwardat, Selin Aviyente, Michigan State University, United States

TA8b-1.9: Graph Signal Processing: Frequency Analysis for Similar Matrices

John Shi, Jose Moura, Carnegie Mellon University, United States

TA8b-1.10: Distributed and Rate-Adaptive Feature Compression

Aditya Deshmukh, Venugopal Veeravalli, University of Illinois Urbana-Champaign, United States; Gunjan Verma, Army Research Laboratory, United States