Publications

• A. Défossez, N. Usunier, L. Bottou, F. Bach. Music Source Separation in the Waveform Domain. Preprint 2019. [preprint] [github] [audio samples]
• A. Défossez, N. Usunier, L. Bottou, F. Bach. Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed. Preprint 2019. [preprint]
• L. Perotin, A. Défossez, E. Vincent, R. Serizel, A. Guérin Regression versus classification for neural network based audio source localization. WASPAA 2019. [paper]
• A. Défossez, N. Zeghidour, N. Usunier, L. Bottou, F. Bach. SING: Symbol-to-Instrument Neural Generator. NIPS 2018. [paper] [github] [poster] [audio samples] [slides].
• A. Défossez, F. Bach. AdaBatch: Efficient Gradient Aggregation Rules for Sequential and Parallel Stochastic Gradient Methods. Preprint 2017. [preprint].
• A. Défossez, F. Bach. Constant step size least-mean-square: Bias-variance trade-offs and optimal sampling distributions. AI Stats 2015. [AI Stats version], [arXiv version].

Interests

Convex and deep learning optimization, stochastic gradient methods, distributed and parallel optimization, audio and music generation. Trying to be a musician.

Teaching

2018

Teaching assistant for the Deep Learning: Do-It-Yourself! class at Ecole Normale Superieure:

• Introduction, 14/09/2018: slides
• Optimization, 26/10/2018: slides, notebook

Other slides

• 2019-01-22: Markov Chains sampling: MCMC and HMC