SPTM-3.5
ADA-STNET: A DYNAMIC ADABOOST SPATIO-TEMPORAL NETWORK FOR TRAFFIC FLOW PREDICTION
Jiawei Sun, Jie Li, Chentao Wu, Zili Tang, Shanghai Jiao Tong University, China; Celimuge Wu, The University of Electro-Communications, Japan
Session:
Graph Representation and Analysis I
Track:
Signal Processing Theory and Methods
Location:
Gather Area M
Presentation Time:
Sun, 8 May, 22:00 - 22:45 China Time (UTC +8)
Sun, 8 May, 14:00 - 14:45 UTC
Sun, 8 May, 14:00 - 14:45 UTC
Session Chair:
Santiago Segarra, Rice University
Session SPTM-3
SPTM-3.1: GRAPHON-AIDED JOINT ESTIMATION OF MULTIPLE GRAPHS
Madeline Navarro, Santiago Segarra, William Marsh Rice University, United States of America
SPTM-3.2: EXPLORING DEEPER GRAPH CONVOLUTIONS FOR SEMI-SUPERVISED NODE CLASSIFICATION
Ashish Tiwari, Shanmuganathan Raman, IIT Gandhinagar, India; Richeek Das, IIT Bombay, India
SPTM-3.3: DYNAMIC PORTFOLIO CUTS: A SPECTRAL APPROACH TO GRAPH-THEORETIC DIVERSIFICATION
Alvaro Arroyo, Bruno Scalzo, Danilo Mandic, Imperial College London, United Kingdom of Great Britain and Northern Ireland; Ljubisa Stankovic, University of Montenegro, United Kingdom of Great Britain and Northern Ireland
SPTM-3.4: STABILITY OF NEURAL NETWORKS ON MANIFOLDS TO RELATIVE PERTURBATIONS
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro, University of Pennsylvania, United States of America
SPTM-3.5: ADA-STNET: A DYNAMIC ADABOOST SPATIO-TEMPORAL NETWORK FOR TRAFFIC FLOW PREDICTION
Jiawei Sun, Jie Li, Chentao Wu, Zili Tang, Shanghai Jiao Tong University, China; Celimuge Wu, The University of Electro-Communications, Japan
SPTM-3.6: LABEL PROPAGATION ACROSS GRAPHS: NODE CLASSIFICATION USING GRAPH NEURAL TANGENT KERNELS
Artun Bayer, Arindam Chowdhury, Santiago Segarra, Rice University, United States of America