Machine Learning

35 publications
October 2021 | CSCW

Let Me Ask You This: How Can a Voice Assistant Elicit Explicit User Feedback?

Ziang Xiao, Sarah Mennicken, Bernd Huber, Adam Shonkoff, Jennifer Thom

September 2021 | ECML-PKDD

Gaussian Process Encoders: VAEs with Reliable Latent-Space Uncertainty

Judith Bütepage, Lucas Maystre, Mounia Lalmas

May 2021 | CHI

Towards Fairness in Practice: A Practitioner-Oriented Rubric for Evaluating Fair ML Toolkits

Brianna Richardson, Jean Garcia-Gathright, Samuel F. Way, Jennifer Thom, Henriette Cramer

April 2021 | The Web Conference

Where To Next? A Dynamic Model of User Preferences

Francesco Sanna Passino, Lucas Maystre, Dmitrii Moor, Ashton Anderson, Mounia Lalmas

April 2021 | AISTATS

Collaborative Classification from Noisy Labels

Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas

March 2021 | WSDM

Shifting Consumption towards Diverse Content on Music Streaming Platforms

Christian Hansen, Rishabh Mehrotra, Casper Hansen, Brian Brost, Lucas Maystre, Mounia Lalmas

December 2020 | NeuRIPS

Model Selection for Production System via Automated Online Experiments

Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Benjamin Carterette, Mounia Lalmas

October 2020 | CIKM

Query Understanding for Surfacing Under-served Music Content

Federico Tomasi, Rishabh Mehrotra, Aasish Pappu, Judith Bütepage, Brian Brost, Hugo Galvão, Mounia Lalmas

September 2020 | RecSys

Contextual and Sequential User Embeddings for Large-Scale Music Recommendation

Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas

August 2020 | KDD

Bandit based Optimization of Multiple Objectives on a Music Streaming Platform

Rishabh Mehrotra, Niannan Xue, Mounia Lalmas

August 2020 | ISMIR - International Society for Music Information Retrieval Conference

Data Cleansing with Contrastive Learning for Vocal Note Event Annotations

Gabriel Meseguer-Brocal, Rachel Bittner, Simon Durand, Brian Brost

August 2020 | Uncertainty in Artificial Intelligence (UAI)

Stochastic Variational Inference for Dynamic Correlated Topic Models

Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas, Zhenwen Dai

July 2020 | IJCAI - International Joint Conference on Artificial Intelligence

Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling

Daniel Stoller, Mi Tian, Sebastian Ewert, and Simon Dixon

July 2020 | WCCI/IJCNN - IEEE World Congress on Computational Intelligence / International Joint Conference on Neural Networks

Using a Neural Network Codec Approximation Loss to Improve Source Separation Performance in Limited Capacity Networks

Ishwarya Ananthabhotla, Sebastian Ewert, Joseph A. Paradiso

April 2020 | ICLR - International Conference on Learning Representations

Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators

Daniel Stoller, Sebastian Ewert, Simon Dixon

October 2019 | ACM MM - ACM International Conference on Multimedia

Towards a Perceptual Loss: Using a Neural Network Codec Approximation as a Loss for Generative Audio Models

Ishwarya Ananthabhotla, Sebastian Ewert, Joseph A. Paradiso

September 2019 | ACM Transactions on Intelligent Systems and Technology

An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation

Hamed Zamani, Markus Schedl, Paul Lamere, Ching-Wei Chen

September 2019 | EUSIPCO

Joint Singing Voice Separation and F0 Estimation with Deep U-Net Architectures

Andreas Jansson, Rachel M Bittner, Sebastian Ewert, Tillman Weyde

July 2019 | ICASSP

End-to-End Lyrics Alignment for Polyphonic Music Using An Audio-to-Character Recognition Model

Daniel Stoller, Simon Durand, Sebastian Ewert