84 citations · 178 across the 15 of their papers we have counts for
16 papers
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing
Blaise Delattre, Alexandre Araujo, Quentin Barthélemy +1
Real-life applications of deep neural networks are hindered by their unsteady predictions when faced with noisy inputs and adversarial attacks. The certified radius in this context…
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech
Titouan Parcollet, Ha Nguyen, Solene Evain +19
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing. Speech processing…
Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration
Blaise Delattre, Quentin Barthélemy, Alexandre Araujo +1
Since the control of the Lipschitz constant has a great impact on the training stability, generalization, and robustness of neural networks, the estimation of this value is nowaday…
A Unified Algebraic Perspective on Lipschitz Neural Networks
Alexandre Araujo, Aaron Havens, Blaise Delattre +2
Important research efforts have focused on the design and training of neural networks with a controlled Lipschitz constant. The goal is to increase and sometimes guarantee the robu…
Experimental study of Neural ODE training with adaptive solver for dynamical systems modeling
Alexandre Allauzen, Thiago Petrilli Maffei Dardis, Hannah Plath
Neural Ordinary Differential Equations (ODEs) was recently introduced as a new family of neural network models, which relies on black-box ODE solvers for inference and training. So…
Curriculum learning for data-driven modeling of dynamical systems
Alessandro Bucci, Onofrio Semeraro, Alexandre Allauzen +2
The reliable prediction of the temporal behavior of complex systems is key in numerous scientific fields. This strong interest is however hindered by modeling issues: often, the go…
A Dynamical System Perspective for Lipschitz Neural Networks
Laurent Meunier, Blaise Delattre, Alexandre Araujo +1
The Lipschitz constant of neural networks has been established as a key quantity to enforce the robustness to adversarial examples. In this paper, we tackle the problem of building…
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
Solene Evain, Ha Nguyen, Hang Le +15
Self-Supervised Learning (SSL) using huge unlabeled data has been successfully explored for image and natural language processing. Recent works also investigated SSL from speech. T…
FlauBERT: Unsupervised Language Model Pre-training for French
Hang Le, Loïc Vial, Jibril Frej +7
Language models have become a key step to achieve state-of-the art results in many different Natural Language Processing (NLP) tasks. Leveraging the huge amount of unlabeled texts…
Empirical Study of Diachronic Word Embeddings for Scarce Data
Syrielle Montariol, Alexandre Allauzen
Word meaning change can be inferred from drifts of time-varying word embeddings. However, temporal data may be too sparse to build robust word embeddings and to discriminate signif…
Learning dynamic word embeddings with drift regularisation
Syrielle Montariol, Alexandre Allauzen
Word usage, meaning and connotation change throughout time. Diachronic word embeddings are used to grasp these changes in an unsupervised way. In this paper, we use variants of the…
Exploring sentence informativeness
Syrielle Montariol, Aina Garí Soler, Alexandre Allauzen
This study is a preliminary exploration of the concept of informativeness -how much information a sentence gives about a word it contains- and its potential benefits to building qu…
Control of chaotic systems by Deep Reinforcement Learning
Michele Alessandro Bucci, Onofrio Semeraro, Alexandre Allauzen +3
Deep Reinforcement Learning (DRL) is applied to control a nonlinear, chaotic system governed by the one-dimensional Kuramoto-Sivashinsky (KS) equation. DRL uses reinforcement learn…
Word Usage Similarity Estimation with Sentence Representations and Automatic Substitutes
Aina Garí Soler, Marianna Apidianaki, Alexandre Allauzen
Usage similarity estimation addresses the semantic proximity of word instances in different contexts. We apply contextualized (ELMo and BERT) word and sentence embeddings to this t…
Towards Recognizing Phrase Translation Processes: Experiments on English-French
Yuming Zhai, Pooyan Safari, Gabriel Illouz +2
When translating phrases (words or group of words), human translators, consciously or not, resort to different translation processes apart from the literal translation, such as Idi…
Document Neural Autoregressive Distribution Estimation
Stanislas Lauly, Yin Zheng, Alexandre Allauzen +1
We present an approach based on feed-forward neural networks for learning the distribution of textual documents. This approach is inspired by the Neural Autoregressive Distribution…