Concept

History of natural language processing

Publications associées (13)

Text Representation Learning for Low Cost Natural Language Understanding

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

EPFL2023

Transformer Models for Vision

Jean-Baptiste Francis Marie Juliette Cordonnier

The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins.All these successful methods depend on a gradient-based learning algorithm to train a model on massive a ...

EPFL2023

Robustness and invariance properties of image classifiers

Apostolos Modas

Deep neural networks have achieved impressive results in many image classification tasks. However, since their performance is usually measured in controlled settings, it is important to ensure that their decisions remain correct when deployed in noisy envi ...

EPFL2022

Learning computationally efficient static word and sentence representations

Prakhar Gupta

Most of the Natural Language Processing (NLP) algorithms involve use of distributed vector representations of linguistic units (primarily words and sentences) also known as embeddings in one way or another. These embeddings come in two flavours namely, sta ...

EPFL2021

Discourse Phenomena in Machine Translation

Lesly Sadiht Miculicich Werlen

Machine Translation (MT) has made considerable progress in the past two decades, particularly after the introduction of neural network models (NMT). During this time, the research community has mostly focused on modeling and evaluating MT systems at the se ...

EPFL2021

Learning Entailment-Based Sentence Embeddings from Natural Language Inference

James Henderson, Rabeeh Karimi Mahabadi, Jan Frederik Jonas Florian Mai

Large datasets on natural language inference are a potentially valuable resource for inducing semantic representations of natural language sentences. But in many such models the embeddings computed by the sentence encoder goes through an MLP-based interact ...

Idiap2019

Simulation-Driven Approach for Business Rules Discovery

Alain Wegmann, Irina Rychkova, Biljana Bajic-Bizumic

Business rules are everywhere. Some of these rules are implicit and thus poorly enforced, others are written but not enforced, and still others are perhaps poorly written and obscurely enforced. In this work, we propose an interactive, simulation-driven ap ...

Springer2013

Computational Methods for Audio-Visual Analysis of Emergent Leadership in Teams

Dairazalia Sanchez Cortes

Face-to-face interactions are part of everyday life, ranging from family to working in teams and to global communities. Social psychologists have long studied these interactions with the aim of understanding behavior, motivations, and emergence of interact ...

EPFL2013

Computational Methods for Audio-Visual Analysis of Emergent Leadership in Teams

Dairazalia Sanchez Cortes

École Polytechnique Fédéral de Lausanne2013

A Survey on Language Modeling using Neural Networks

Nikolaos Pappas, Thomas Meyer

A Language Model (LM) is a helpful component of a variety of Natural Language Processing (NLP) systems today. For speech recognition, machine translation, information retrieval, word sense disambiguation etc., the contribution of an LM is to provide featur ...

Idiap2012

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