2 citations · 3 across the 5 of their papers we have counts for
5 papers
Top- Pareto Bandits: Hypervolume Regret for Multi-Objective Slate Selection
Nicolas Gutowski, Fabien Chhel, Alexandre Letard +1
We consider a stochastic multi-objective bandit problem where, at each round, the agent selects a slate of arms and observes their -dimensional reward vectors under semi-ban…
miditok: A Python package for MIDI file tokenization
Nathan Fradet, Jean-Pierre Briot, Fabien Chhel +2
Recent progress in natural language processing has been adapted to the symbolic music modality. Language models, such as Transformers, have been used with symbolic music for a vari…
Impact of time and note duration tokenizations on deep learning symbolic music modeling
Nathan Fradet, Nicolas Gutowski, Fabien Chhel +1
Symbolic music is widely used in various deep learning tasks, including generation, transcription, synthesis, and Music Information Retrieval (MIR). It is mostly employed with disc…
Byte Pair Encoding for Symbolic Music
Nathan Fradet, Nicolas Gutowski, Fabien Chhel +1
When used with deep learning, the symbolic music modality is often coupled with language model architectures. To do so, the music needs to be tokenized, i.e. converted into a seque…
Partial Bandit and Semi-Bandit: Making the Most Out of Scarce Users' Feedback
Alexandre Letard, Tassadit Amghar, Olivier Camp +1
Recent works on Multi-Armed Bandits (MAB) and Combinatorial Multi-Armed Bandits (COM-MAB) show good results on a global accuracy metric. This can be achieved, in the case of recomm…