works on

From the 1 of 1.7k papers with an AI index.

output
20052026
most citedBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

24.4k citations

Showing 2014 · cs.CLShow all

6 papers · 2 filters

cs.CL2014404 cited

Grammar as a Foreign Language

Oriol Vinyals, Lukasz Kaiser, Terry Koo +3

Syntactic constituency parsing is a fundamental problem in natural language processing and has been the subject of intensive research and engineering for decades. As a result, the…

cs.CL201485 cited

Extraction of Salient Sentences from Labelled Documents

Misha Denil, Alban Demiraj, Nando de Freitas

We present a hierarchical convolutional document model with an architecture designed to support introspection of the document structure. Using this model, we show how to use visual…

cs.CL201495 cited

Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews

Grégoire Mesnil, Tomas Mikolov, Marc'Aurelio Ranzato +1

Sentiment analysis is a common task in natural language processing that aims to detect polarity of a text document (typically a consumer review). In the simplest settings, we discr…

cs.CL201413.4k cited

Sequence to Sequence Learning with Neural Networks

Ilya Sutskever, Oriol Vinyals, Quoc V. Le

Deep Neural Networks (DNNs) are powerful models that have achieved excellent performance on difficult learning tasks. Although DNNs work well whenever large labeled training sets a…

cs.CL20145.1k cited

Distributed Representations of Sentences and Documents

Quoc V. Le, Tomas Mikolov

Many machine learning algorithms require the input to be represented as a fixed-length feature vector. When it comes to texts, one of the most common fixed-length features is bag-o…

cs.CL201486 cited

Open Question Answering with Weakly Supervised Embedding Models

Antoine Bordes, Jason Weston, Nicolas Usunier

Building computers able to answer questions on any subject is a long standing goal of artificial intelligence. Promising progress has recently been achieved by methods that learn t…