159 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of BathGB2 papers
- Centre National de la Recherche ScientifiqueFR1 paper
- Complejo Hospitalario de CáceresES1 paper
- East China Normal UniversityCN1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- LIP6FR1 paper
- New York UniversityUS1 paper
- Photon Spot (United States)US1 paper
- Purdue University West LafayetteUS1 paper
- Sorbonne UniversitéFR1 paper
- Technical University of MunichDE1 paper
- The Alan Turing InstituteGB1 paper
10 papers
Bootstrapping Conversational Recommendation Agents At Spotify: Synthetic Data Generation and Self-Improvement Loops
Enrico Palumbo, Alexandre Tamborrino, Victor Ode +15
Conversational recommendation agents are a new paradigm for content discovery, enabling users to express complex intents through natural language (e.g., "recommend Italian indie ar…
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms
Yanhao Wang, Michael Mathioudakis, Jia Li +1
Diversity maximization aims to select a diverse and representative subset of items from a large dataset. It is a fundamental optimization task that finds applications in data summa…
Cem Mil Podcasts: A Spoken Portuguese Document Corpus For Multi-modal, Multi-lingual and Multi-Dialect Information Access Research
Ekaterina Garmash, Edgar Tanaka, Ann Clifton +5
In this paper we describe the Portuguese-language podcast dataset we have released for academic research purposes. We give an overview of how the data was sampled, descriptive stat…
Black-box density function estimation using recursive partitioning
Erik Bodin, Zhenwen Dai, Neill D. F. Campbell +1
We present a novel approach to Bayesian inference and general Bayesian computation that is defined through a sequential decision loop. Our method defines a recursive partitioning o…
Feature Selection Methods for Uplift Modeling and Heterogeneous Treatment Effect
Zhenyu Zhao, Yumin Zhang, Totte Harinen +1
Uplift modeling is a causal learning technique that estimates subgroup-level treatment effects. It is commonly used in industry and elsewhere for tasks such as targeting ads. In a…
Deep Unsupervised Drum Transcription
Keunwoo Choi, Kyunghyun Cho
We introduce DrummerNet, a drum transcription system that is trained in an unsupervised manner. DrummerNet does not require any ground-truth transcription and, with the data-scalab…
Modulating Surrogates for Bayesian Optimization
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite +3
Bayesian optimization (BO) methods often rely on the assumption that the objective function is well-behaved, but in practice, this is seldom true for real-world objectives even if…
Scalable and Efficient Comparison-based Search without Features
Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser
We consider the problem of finding a target object using pairwise comparisons, by asking an oracle questions of the form \emph{"Which object from the pair is more simil…
The Skipping Behavior of Users of Music Streaming Services and its Relation to Musical Structure
Nicola Montecchio, Pierre Roy, François Pachet
The behavior of users of music streaming services is investigated from the point of view of the temporal dimension of individual songs; specifically, the main object of the analysi…
Music Generation by Deep Learning - Challenges and Directions
Jean-Pierre Briot, François Pachet
In addition to traditional tasks such as prediction, classification and translation, deep learning is receiving growing attention as an approach for music generation, as witnessed…