Our research activity focused on developing novel adaptive strategies for large-scale networks with applications including adaptive streaming strategies for virtual reality services, data-efficient multi-arm bandit problems for online recommendation systems, graph-based reinforcement learning for AI systems, and influence maximization over social networks. Our research is at the crossroad between multimedia processing, machine learning, and signal processing.
Have you just finished your PhD and are you looking for a new position? Or are you just wondering how you can join us? Here, some ideas that can help you 🙂 1. Newton International Fellowship Scheme 2020 This scheme is jointly run by the British Academy, the Academy of Medical Sciences and the Royal Society. The NewtonContinue Reading
Title: “Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms”Authors: Gholamali Aminian, Laura Toni, and Miguel Rodrigues Link: https://arxiv.org/pdf/2010.12664v1.pdf Abstract: Generalization error bounds are critical to under- standing the performance of machine learning models. In this work, we propose a new information-theoretic based general- ization error upper bound applicable to supervised learning scenarios. We show that our generalContinue Reading
20.09.2020: New paper accepted to IEEE Signal Processing Letter. Title: “Large Database Compression Based on Perceived Information” Authors: Thomas Maugey, Laura Toni Link: inria repository, IEEExplore early access Abstract: Lossy compression algorithms trade bits for quality,aiming at reducing as much as possible the bitrate needed to represent the original source (or set of sources), while preservingContinue Reading
Check our opening page, there is always an opportunity if you want to join us 🙂