4.6k citations · 7.9k across the 144 of their papers we have counts for
11 papers · 1 filter
Supervised Linear Regression for Graph Learning from Graph Signals
Arun Venkitaraman, Hermina Petric Maretic, Saikat Chatterjee +1
We propose a supervised learning approach for predicting an underlying graph from a set of graph signals. Our approach is based on linear regression. In the linear regression model…
IRSA Transmission Optimization via Online Learning
Laura Toni, Pascal Frossard
In this work, we propose a new learning framework for optimising transmission strategies when irregular repetition slotted ALOHA (IRSA) MAC protocol is considered. We cast the onli…
Graph Transform Optimization with Application to Image Compression
Giulia Fracastoro, Dorina Thanou, Pascal Frossard
In this paper, we propose a new graph-based transform and illustrate its potential application to signal compression. Our approach relies on the careful design of a graph that opti…
Finite Length Performance of Random Slotted ALOHA Strategies
Konstantinos Dovelos, Laura Toni, Pascal Frossard
Multiple connected devices sharing common wireless resources might create interference if they access the channel simultaneously. Medium access control (MAC) protocols gener- ally…
Prioritized Random MAC Optimization via Graph-based Analysis
Laura Toni, Pascal Frossard
Motivated by the analogy between successive interference cancellation and iterative belief-propagation on erasure channels, irregular repetition slotted ALOHA (IRSA) strategies hav…
Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery from Multiple Servers
Nikolaos Thomos, Eymen Kurdoglu, Pascal Frossard +1
In this paper, we deal with the problem of jointly determining the optimal coding strategy and the scheduling decisions when receivers obtain layered data from multiple servers. Th…