activity
20172022
most citedCorrupt Bandits for Preserving Local Privacy

19 citations · 36 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2022

Graph Neural Network Policies and Imitation Learning for Multi-Domain Task-Oriented Dialogues

Thibault Cordier, Tanguy Urvoy, Fabrice Lefèvre +1

Task-oriented dialogue systems are designed to achieve specific goals while conversing with humans. In practice, they may have to handle simultaneously several domains and tasks. T…

cs.CL20206 cited

Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF Verbalization with Transformers

Sebastien Montella, Betty Fabre, Tanguy Urvoy +2

The task of verbalization of RDF triples has known a growth in popularity due to the rising ubiquity of Knowledge Bases (KBs). The formalism of RDF triples is a simple and efficien…

cs.CL20202 cited

Diluted Near-Optimal Expert Demonstrations for Guiding Dialogue Stochastic Policy Optimisation

Thibault Cordier, Tanguy Urvoy, Lina M. Rojas-Barahona +1

A learning dialogue agent can infer its behaviour from interactions with the users. These interactions can be taken from either human-to-human or human-machine conversations. Howev…

cs.LG20199 cited

Budgeted Reinforcement Learning in Continuous State Space

Nicolas Carrara, Edouard Leurent, Romain Laroche +3

A Budgeted Markov Decision Process (BMDP) is an extension of a Markov Decision Process to critical applications requiring safety constraints. It relies on a notion of risk implemen…

cs.LG201719 cited

Corrupt Bandits for Preserving Local Privacy

Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann

We study a variant of the stochastic multi-armed bandit (MAB) problem in which the rewards are corrupted. In this framework, motivated by privacy preservation in online recommender…