5.2k citations · 8.2k across the 49 of their papers we have counts for
7 papers · 1 filter
Simple Image Description Generator via a Linear Phrase-Based Approach
Remi Lebret, Pedro O. Pinheiro, Ronan Collobert
Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model…
Learning linearly separable features for speech recognition using convolutional neural networks
Dimitri Palaz, Mathew Magimai Doss, Ronan Collobert
Automatic speech recognition systems usually rely on spectral-based features, such as MFCC of PLP. These features are extracted based on prior knowledge such as, speech perception…
Joint RNN-Based Greedy Parsing and Word Composition
Joël Legrand, Ronan Collobert
This paper introduces a greedy parser based on neural networks, which leverages a new compositional sub-tree representation. The greedy parser and the compositional procedure are j…
Video (language) modeling: a baseline for generative models of natural videos
MarcAurelio Ranzato, Arthur Szlam, Joan Bruna +3
We propose a strong baseline model for unsupervised feature learning using video data. By learning to predict missing frames or extrapolate future frames from an input video sequen…
N-gram-Based Low-Dimensional Representation for Document Classification
Rémi Lebret, Ronan Collobert
The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of f…
Rehabilitation of Count-based Models for Word Vector Representations
Rémi Lebret, Ronan Collobert
Recent works on word representations mostly rely on predictive models. Distributed word representations (aka word embeddings) are trained to optimally predict the contexts in which…