MA3b.2

A Hierarchical Approach to Multitask Learning Over Networks

Aaron Fainman, Stefan Vlaski, Imperial College London, United Kingdom
Session:
MA3b: Learning over Networks Lecture
Track:
Networks and Graphs
Location:
Room 3
Presentation Time:
Mon, 26 Oct, 10:40 - 11:05 PT (UTC -7)
Session Chair:
Paolo Di Lorenzo, Sapienza Università di Roma, Italy
Presentation
Discussion
Resources
No resources available.
Session MA3b
MA3b.1: Learning Graph Signal Generative Models
Yigit Berkay Uslu, Samar Hadou, University of Pennsylvania, United States; Sergio Rozada, King Juan Carlos University, Spain; Shirin Saeedi Bidokhti, Alejandro Ribeiro, University of Pennsylvania, United States
MA3b.2: A Hierarchical Approach to Multitask Learning Over Networks
Aaron Fainman, Stefan Vlaski, Imperial College London, United Kingdom
MA3b.3: Bayesian Graph Learning via Langevin Dynamics with Tractable Proximity Priors
Victor M. Tenorio, King Juan Carlos University, Spain; Santiago Segarra, Rice University, United States; Antonio G. Marques, King Juan Carlos University, Spain
MA3b.4: Inverse Cross-spectral Neural Networks for Multivariate Time Series
Lorenzo Marinucci, Leonardo Di Nino, Gabriele D'Acunto, Paolo Di Lorenzo, Sergio Barbarossa, Sapienza University of Rome, Italy
Contacts