- Centre National de la Recherche ScientifiqueFR1 paper
- Entrepôts, Représentation et Ingénierie des ConnaissancesFR1 paper
- Institut de Recherche en Informatique et Systèmes AléatoiresFR1 paper
- Institut für Regionale Innovation und SozialforschungDE1 paper
- Institut Universitaire de FranceFR1 paper
- Laboratoire d'Informatique de Paris-NordFR1 paper
- Laboratoire Lorrain de Recherche en Informatique et ses ApplicationsFR1 paper
- Lyon 1 UniversitéFR1 paper
- Omron (Japan)JP1 paper
- TU Dortmund UniversityDE1 paper
- Université de BordeauxFR1 paper
- Université Lumière Lyon 2FR1 paper
6 papers
Diffusion-Based Multi-Class Normality for OOD Detection: An Application to CDP Authentication
Bolutife Atoki, Iuliia Tkachenko, Bertrand Kerautret +1
Reconstruction-based generative models offer a natural framework for unsupervised out-of-distribution (OOD) detection, but multi-class normality modelling requires a single detecto…
The Bright Side of Timed Opacity
Ãtienne André, Sarah Dépernet, Engel Lefaucheux
Timed automata (TAs) are an extension of finite automata that can measure and react to the passage of time, providing the ability to handle real-time constraints using clocks. In 2…
Work-Efficient Query Evaluation in Constant Time with PRAMs
Jens Keppeler, Thomas Schwentick, Christopher Spinrath
The article studies query evaluation in parallel constant time in the CRCW PRAM model. While it is well-known that all relational algebra queries can be evaluated in constant time…
PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
Abdelkrim Zitouni, Mehdi Hennequin, Juba Agoun +3
We derive a novel PAC-Bayesian generalization bound for reinforcement learning that explicitly accounts for Markov dependencies in the data, through the chain's mixing time. This c…
Instance Discrimination for Link Prediction
Valentin Cuzin-Rambaud, Mathieu Lefort, Rémy Cazabet
Recently, instance discrimination models have emerged as a major solution for self-supervised learning. Having already demonstrated its effectiveness in the image domain, instance…
A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication
Valentin Cuzin-Rambaud, Laetitia Matignon, Maxime Morge
In multi-agent reinforcement learning (MARL), the integration of a communication mechanism, allowing agents to better learn to coordinate their actions and converge on their object…