About me
- Alexandre Défossez, defossez at fb.com.
- Research scientist at FAIR Paris
-
Formerly
CIFRE PhD student at FAIR Paris and
Sierra at INRIA Paris,
under the supervision of Léon Bottou (FAIR), Nicolas Usunier (FAIR) and Francis Bach (INRIA).
-
[scholar]
[github]
[twitter]
Interests
Convex and non convex optimization, stochastic gradient methods, source separation, audio processing and synthesis.
Amateur DJ and composer [soundcloud].
Publications
-
A. Défossez, G. Synnaeve, Y. Adi.
Real Time Speech Enhancement in the Waveform Domain.
Interspeech 2020.
[preprint]
[audio samples]
[code]
-
A. Défossez, L. Bottou, F. Bach, N. Usunier.
On the Convergence of Adam and Adagrad. Preprint 2020.
[preprint]
-
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].
Teaching
2018
Teaching assistant for the
Deep Learning: Do-It-Yourself!
class at Ecole Normale Superieure: