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Concept

Computational linguistics

Related publications (31)

Graph-to-Graph Transformer for Transition-based Dependency Parsing

James Henderson, Alireza Mohammadshahi

We propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models of transition-based dependenc ...

Association for Computational Linguistics2020

Mixed-Precision Deep Learning Based on Computational Memory

Irem Boybat Kara, Abu Sebastian

Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...

FRONTIERS MEDIA SA2020

Microneurography as a tool to develop decoding algorithms for peripheral neuro-controlled hand prostheses

Silvestro Micera, Marco Capogrosso, Stanisa Raspopovic, Francesco Maria Petrini, Jacopo Rigosa

Background:The usability of dexterous hand prostheses is still hampered by the lack of natural and effective control strategies. A decoding strategy based on the process-ing of descending efferent neural signals recorded using peripheral neural interfaces ...

2019

Phase-Change Memory Models for Deep Learning Training and Inference

Irem Boybat Kara, Abu Sebastian

Non-volatile analog memory devices such as phase-change memory (PCM) enable designing dedicated connectivity matrices for the hardware implementation of deep neural networks (DNN). In this in-memory computing approach, the analog conductance states of the ...

IEEE2019

A Representer Theorem for Deep Neural Networks

Michaël Unser

We propose to optimize the activation functions of a deep neural network by adding a corresponding functional regularization to the cost function. We justify the use of a second-order total-variation criterion. This allows us to derive a general represente ...

2019

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

Christian O'Reilly, Elisabetta Iavarone

The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousa ...

Springer2019

Computing Crowd Consensus with Partial Agreement (Extended Abstract)

Quoc Viet Hung Nguyen, Thành Tâm Nguyên

Crowdsourcing has been widely established as a means to enable human computation at large-scale, in particular for tasks that require manual labelling of large sets of data items. Answers obtained from heterogeneous crowd workers are aggregated to obtain a ...

IEEE2018

Interactions of spatial strategies producing generalization gradient and blocking: A computational approach

Ricardo Andres Chavarriaga Lozano

We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different varia ...

2018

Mixed-precision architecture based on computational memory for training deep neural networks

Irem Boybat Kara, Abu Sebastian

Deep neural networks (DNN) have revolutionized the field of machine learning by providing unprecedented human-like performance in solving many real-world problems such as image or speech recognition. Training of large DNNs, however, is a computationally in ...

IEEE2018

We get the algorithms of our ground truths: Designing referential databases in digital image processing

Florian Lucas Jaton

This article documents the practical efforts of a group of scientists designing an imageprocessing algorithm for saliency detection. By following the actors of this computer science project, the article shows that the problems often considered to be the st ...

SAGE Publications2017

Studying Linguistic Changes over 200 Years of Newspapers through Resilient Words Analysis

Frédéric Kaplan, Cyril Antoine Michel Bornet, Vincent Christian Buntinx

This paper presents a methodology to analyze linguistic changes in a given textual corpus allowing to overcome two common problems related to corpus linguistics studies. One of these issues is the monotonic increase of the corpus size with time, and the ot ...

2017