1.2k citations
- Centre National de la Recherche ScientifiqueFR14 papers
- Institut national de recherche en sciences et technologies du numériqueFR14 papers
- National Institute of InformaticsJP13 papers
- SupélecFR13 papers
- University of Illinois ChicagoUS10 papers
- Technical University of MunichDE9 papers
- Laboratoire Informatique d'AvignonFR8 papers
- University College LondonGB8 papers
- University of EdinburghGB8 papers
- Sorbonne UniversitéFR7 papers
- Université Côte d'AzurFR7 papers
- University of Eastern FinlandFI7 papers
7 papers · 2 filters
Deep Reinforcement Learning for Resource Constrained Multiclass Scheduling in Wireless Networks
Apostolos Avranas, Marios Kountouris, Philippe Ciblat
The problem of resource constrained scheduling in a dynamic and heterogeneous wireless setting is considered here. In our setup, the available limited bandwidth resources are alloc…
An Identifiable Double VAE For Disentangled Representations
Graziano Mita, Maurizio Filippone, Pietro Michiardi
A large part of the literature on learning disentangled representations focuses on variational autoencoders (VAE). Recent developments demonstrate that disentanglement cannot be ob…
Many-to-one Recurrent Neural Network for Session-based Recommendation
Amine Dadoun, Raphael Troncy
This paper presents the D2KLab team's approach to the RecSys Challenge 2019 which focuses on the task of recommending accommodations based on user sessions. What is the feeling of…
Two Stages Approach for Tweet Engagement Prediction
Amine Dadoun, Ismail Harrando, Pasquale Lisena +2
This paper describes the approach proposed by the D2KLab team for the 2020 RecSys Challenge on the task of predicting user engagement facing tweets. This approach relies on two dis…
UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach
Harald Bayerlein, Mirco Theile, Marco Caccamo +1
Autonomous deployment of unmanned aerial vehicles (UAVs) supporting next-generation communication networks requires efficient trajectory planning methods. We propose a new end-to-e…
Isotropic SGD: a Practical Approach to Bayesian Posterior Sampling
Giulio Franzese, Rosa Candela, Dimitrios Milios +2
In this work we define a unified mathematical framework to deepen our understanding of the role of stochastic gradient (SG) noise on the behavior of Markov chain Monte Carlo sampli…