M
Manuel Montes-y-Gómez
Researcher at National Institute of Astrophysics, Optics and Electronics
Publications - 207
Citations - 3403
Manuel Montes-y-Gómez is an academic researcher from National Institute of Astrophysics, Optics and Electronics. The author has contributed to research in topics: Question answering & Computer science. The author has an hindex of 28, co-authored 192 publications receiving 2786 citations. Previous affiliations of Manuel Montes-y-Gómez include Instituto Politécnico Nacional.
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Gated Multimodal Units for Information Fusion
TL;DR: In this paper, a novel model for multimodal learning based on gated neural networks is presented, which is intended to be used as an internal unit in a neural network architecture whose purpose is to find an intermediate representation based on a combination of data from different modalities.
Journal ArticleDOI
Detecting positive and negative deceptive opinions using PU-learning
TL;DR: A novel method is proposed that with respect to its original version is much more conservative at the moment of selecting the negative examples from the unlabeled ones and consistently outperformed the original PU-learning approach in the detection of positive and negative deceptive opinions respectively.
Overview of the 6th Author Profiling Task at PAN 2018: Multimodal Gender Identification in Twitter.
TL;DR: This overview presents the framework and the results of the Author Profiling shared task at PAN 2018, to address gender identification from a multimodal perspective, where not only texts but also images are given.
Journal ArticleDOI
A Text Classification Framework for Simple and Effective Early Depression Detection Over Social Media Streams
TL;DR: SS3 was designed to be used as a general framework to deal with ERD problems and evaluated on the CLEF’s eRisk2017 pilot task on early depression detection, showing that the classifier was able to outperform these models and standard classifiers, despite being less computationally expensive and having the ability to explain its rationale.
Proceedings Article
Gated Multimodal Units for Information Fusion
TL;DR: The Gated Multimodal Unit model is intended to be used as an internal unit in a neural network architecture whose purpose is to find an intermediate representation based on a combination of data from different modalities.