BackExaminar Comunicaciones por departamento (cas.) "Ciencia de la computación e inteligencia artificial"
Now showing items 1-13 of 13
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Characterising the rankings produced by combinatorial optimisation problems and finding their intersections.
Hernando Rodríguez, Leticia
; ; (Association for Computing Machinery, 2019-07)
[EN] The aim of this paper is to introduce the concept of intersection between combinatorial optimisation problems. We take into account that most algorithms, in their machinery, do not consider the exact objective function ... -
Envisioning the Benefits of Back-Drive in Evolutionary Algorithms
Garciarena Hualde, Unai; ; Santana Hermida, Roberto (IEEE, 2020-09-03)
Among the characteristics of traditional evolutionary algorithms governed by models, memory volatility is one of the most frequent. This is commonly due to the limitations of the models used to guide this kind of algorithms, ... -
Evolved GANs for generating Pareto set approximations
Garciarena Hualde, Unai; ; Santana Hermida, Roberto (ACM, 2018-07-02)
In machine learning, generative models are used to create data samples that mimic the characteristics of the training data. Generative adversarial networks (GANs) are neural-network based generator models that have shown ... -
Mental Health Monitoring from Speech and Language
; Justo Blanco, Raquel; ; De Velasco Vázquez, Mikel (ISCA, 2022)
Concern for mental health has increased in the last years due to its impact in people life quality and its consequential effect on healthcare systems. Automatic systems that can help in the diagnosis, symptom monitoring, ... -
Multimodal feature evaluation and fusion for emotional well-being monitorization
; Justo Blanco, Raquel (Springer, 2022-04-26)
Mental health is a global issue that plays an important roll in the overall well-being of a person. Because of this, it is important to preserve it, and conversational systems have proven to be helpful in this task. This ... -
SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability
Agirre Bengoa, Eneko; ; ; ; ; ; ; López Gazpio, Iñigo ; Marichalar Anglada, Montserrat ; ; Rigau Claramunt, Germán ; Uria Garin, Larraitz ; (SemEval, 2015)
In semantic textual similarity (STS), systems rate the degree of semantic equivalence between two text snippets. This year, the participants were challenged with new datasets in English and Spanish. The annotations for ... -
Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation
; ; Agirre Bengoa, Eneko; López Gazpio, Iñigo ; (ACL, 2017-08)
Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, ... -
Service-independent payload analysis to improve intrusion detection in network traffic
; Gurrutxaga Goikoetxea, Ibai; ; ; ; Pérez de la Fuente, Jesús María (ACM, 2008-11-27)
The popularity of computer networks broadens the scope for network attackers and increases the damage these attacks can cause. In this context, Intrusion Detection Systems (IDS) are included as part of any complete security ... -
Singing minstrel robots, a means for improving social behaviors
Rodríguez Rodríguez, Igor; ; ; (IEEE, 2016-06-06)
Bertsolaritza, Basque improvised contest poetry, offers another sphere to develop robot body language and robot communication capabilities, that shares some similarities with theatrical performances. It is also a new area ... -
Speech emotion recognition in Spanish TV Debates
; Justo Blanco, Raquel; De Velasco Vázquez, Mikel ; Torres Barañano, María Inés (ISCA, 2022)
Emotion recognition from speech is an active field of study that can help build more natural human-machine interaction systems. Even though the advancement of deep learning technology has brought improvements in this task, ... -
Superpixel Mixing: A Data Augmentation Technique For Robust Deep Visual Recognition Models
(IEEE, 2024-09-27)Data augmentation can mitigate overfitting problems in data exploration without increasing the size of the model. Existing cutmix-based data augmentation has been proven to signifi- cantly enhance deep learning ... -
Transfer learning in hierarchical dialogue topic classification with neural networks
Montenegro Portillo, César; Santana Hermida, Roberto; (IEEE, 2020-09-28)
Knowledge transfer between tasks can significantly improve the efficiency of machine learning algorithms. In supervised natural language understanding problems, this sort of improvement is critical since the availability ... -
Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation
; Labaka Intxauspe, Gorka; López Gazpio, Iñigo ; Agirre Bengoa, Eneko (ACL, 2018)
Following the recent success of word embeddings, it has been argued that there is no such thing as an ideal representation for words, as different models tend to capture divergent and often mutually incompatible aspects ...