58 citations · 81 across the 5 of their papers we have counts for
6 papers
Deep Recurrent Encoder: A scalable end-to-end network to model brain signals
Omar Chehab, Alexandre Defossez, Jean-Christophe Loiseau +2
Understanding how the brain responds to sensory inputs is challenging: brain recordings are partial, noisy, and high dimensional; they vary across sessions and subjects and they ca…
Real Time Speech Enhancement in the Waveform Domain
Alexandre Defossez, Gabriel Synnaeve, Yossi Adi
We present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with…
Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed
Alexandre Défossez, Nicolas Usunier, Léon Bottou +1
We study the problem of source separation for music using deep learning with four known sources: drums, bass, vocals and other accompaniments. State-of-the-art approaches predict s…
SING: Symbol-to-Instrument Neural Generator
Alexandre Défossez, Neil Zeghidour, Nicolas Usunier +2
Recent progress in deep learning for audio synthesis opens the way to models that directly produce the waveform, shifting away from the traditional paradigm of relying on vocoders…
AdaBatch: Efficient Gradient Aggregation Rules for Sequential and Parallel Stochastic Gradient Methods
Alexandre Défossez, Francis Bach
We study a new aggregation operator for gradients coming from a mini-batch for stochastic gradient (SG) methods that allows a significant speed-up in the case of sparse optimizatio…
Constant Step Size Least-Mean-Square: Bias-Variance Trade-offs and Optimal Sampling Distributions
Alexandre Défossez, Francis Bach
We consider the least-squares regression problem and provide a detailed asymptotic analysis of the performance of averaged constant-step-size stochastic gradient descent (a.k.a. le…