Oscar Luaces

发表

Deep learning to frame objects for visual target tracking

Zhezhou Yu, Shu-Chao Pang, Juan José del Coz, 2017, Eng. Appl. Artif. Intell..

Analysis of nutrition data by means of a matrix factorization method

Thorsten Joachims, Oscar Luaces, Jorge Díez, 2015, Progress in Artificial Intelligence.

Adapting Decision DAGs for Multipartite Ranking

Elena Montañés, José Ramón Quevedo, Juan José del Coz, 2010, ECML/PKDD.

Machine Learning Usefulness Relies on Accuracy and Self-Maintenance

José Ranilla, Enrique A. de la Cal, Oscar Luaces, 1998, IEA/AIE.

Clustering people according to their preference criteria

Juan José del Coz, Oscar Luaces, Jorge Díez, 2008, Expert Syst. Appl..

Improving recommender systems by encoding items and user profiles considering the order in their consumption history

Oscar Luaces, Antonio Bahamonde, Jorge Díez, 2019, Progress in Artificial Intelligence.

Feature subset selection for learning preferences: a case study

José Ramón Quevedo, Juan José del Coz, Oscar Luaces, 2004, ICML.

Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM

Juan José del Coz, Oscar Luaces, Jorge Díez, 2004, NIPS.

Multilabel classifiers with a probabilistic thresholding strategy

José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde, 2012, Pattern Recognit..

How to learn consumer preferences from the analysis of sensory data by means of support vector machines (SVM)

José Ramón Quevedo, Juan José del Coz, Oscar Luaces, 2007 .

Aplicacion de un proceso de seleccion de reglas a un sistema de aprendizaje

José Ranilla, Oscar Luaces, Jorge Díez Peláez, 2002, Inteligencia Artif..

Binary relevance efficacy for multilabel classification

Juan José del Coz, Oscar Luaces, Antonio Bahamonde, 2012, Progress in Artificial Intelligence.

Un sistema inteligente para calificar morfológicamente a bovinos de la raza Asturiana de los Valles

José Ranilla, José Ramón Quevedo, F. López, 2000, Inteligencia Artif..

A heuristic for learning decision trees and pruning them into classification rules

José Ranilla, Oscar Luaces, Antonio Bahamonde, 2003, AI Commun..

Graphical Feature Selection for Multilabel Classification Tasks

José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde, 2011, IDA.

Towards explainable personalized recommendations by learning from users' photos

Oscar Luaces, Antonio Bahamonde, Beatriz Remeseiro, 2020, Inf. Sci..

Using tensor products to detect unconditional label dependence in multilabel classifications

Juan José del Coz, Oscar Luaces, Antonio Bahamonde, 2016, Inf. Sci..

Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models

José Ramón Quevedo, Juan José del Coz, Oscar Luaces, 2010, J. Comput. Biol..

Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis

José Ramón Quevedo, Juan José del Coz, Oscar Luaces, 2004, ECAI.

Interval prediction for graded multi-label classification

Oscar Luaces, Antonio Bahamonde, Gerardo Lastra, 2014, Pattern Recognit. Lett..

A clustering algorithm to find groups with homogeneous preferences1

Juan José del Coz, Oscar Luaces, Jorge Díez, 2003 .

Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection

José Ramón Quevedo, Juan José del Coz, Oscar Luaces, 2004, ECML.

Optimizing different loss functions in multilabel classifications

Juan José del Coz, Oscar Luaces, Jorge Díez, 2014, Progress in Artificial Intelligence.

Aprendizaje de la Similitud entre Casos con Valores Discretos y Numericos (Premio Accésit Jose Cuena)

Oscar Luaces, Antonio Bahamonde, A. Bahamonde, 2000, Inteligencia Artif..

Combining Deep Learning and Preference Learning for Object Tracking

Zhezhou Yu, Shu-Chao Pang, Juan José del Coz, 2016, ICONIP.

A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments

Amparo Alonso-Betanzos, Alicia Troncoso Lora, Oscar Luaces, 2015, Knowl. Based Syst..

Prediction of Probability of Survival in Critically Ill Patients Optimizing the Area under the ROC Curve

José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde, 2007, IJCAI.

Including Content-Based Methods in Peer-Assessment of Open-Response Questions

Amparo Alonso-Betanzos, Alicia Troncoso Lora, Oscar Luaces, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Predicting the probability of survival in intensive care unit patients from a small number of variables and training examples

Oscar Luaces, Antonio Bahamonde, Francisco Taboada, 2009, Artif. Intell. Medicine.

Self-Organizing Cases to Find Paradigms

José Ranilla, José Ramón Quevedo, Juan José del Coz, 1999, IWANN.

Using artificial intelligence to design and implement a morphological assessment system in beef cattle

José Ranilla, José Ramón Quevedo, Oscar Luaces, 2001 .

Learning to Predict One or More Ranks in Ordinal Regression Tasks

Juan José del Coz, Oscar Luaces, Jorge Díez, 2008, ECML/PKDD.

Analysis of clinical prognostic variables for Chronic Lymphocytic Leukemia decision-making problems

Enrique J. deAndrés-Galiana, Oscar Luaces, Juan Luis Fernández Martínez, 2016, J. Biomed. Informatics.

Viability of an Alarm Predictor for Coffee Rust Disease Using Interval Regression

José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde, 2010, IEA/AIE.

Inflating examples to obtain rules

Oscar Luaces, Antonio Bahamonde, A. Bahamonde, 2003, Int. J. Intell. Syst..

Mapping preferences into Euclidean space

Thorsten Joachims, Oscar Luaces, Jorge Díez, 2015, Expert Syst. Appl..

Deep Learning and Preference Learning for Object Tracking: A Combined Approach

Zhezhou Yu, Shu-Chao Pang, Juan José del Coz, 2017, Neural Processing Letters.

A simple and efficient method for variable ranking according to their usefulness for learning

José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde, 2007, Comput. Stat. Data Anal..

Content-based methods in peer assessment of open-response questions to grade students as authors and as graders

Alicia Troncoso Lora, Amparo Alonso-Betanzos, Oscar Luaces, 2017, Knowl. Based Syst..

Autonomous Clustering for Machine Learning

José Ranilla, José Ramón Quevedo, Juan José del Coz, 1999, IWANN.

The usefulness of artificial intelligence techniques to assess subjective quality of products in the food industry

José Ranilla, José Ramón Quevedo, Oscar Luaces, 2001 .

Advances in Artificial Intelligence

Emilio Corchado, Mikel Galar, Héctor Quintián, 2016, Lecture Notes in Computer Science.

Using nondeterministic learners to alert on coffee rust disease

Oscar Luaces, Antonio Bahamonde, Carlos Alberto Alves Meira, 2011, Expert Syst. Appl..

A new method to learn growth curves of beef cattle using a factorization approach

Oscar Luaces, Jorge Díez, Jaime Alonso, 2018, Comput. Electron. Agric..

Optimizing novelty and diversity in recommendations

Amparo Alonso-Betanzos, David Martínez-Rego, Oscar Luaces, 2018, Progress in Artificial Intelligence.

Feature selection for classification of animal feed ingredients from near infrared microscopy spectra

Elena Montañés, José Ramón Quevedo, Oscar Luaces, 2013, Inf. Sci..

Soft Margin Trees

Juan José del Coz, Oscar Luaces, Jorge Díez, 2009, ECML/PKDD.

A peer assessment method to provide feedback, consistent grading and reduce students' burden in massive teaching settings

Oscar Luaces, Jorge Díez, Antonio Bahamonde, 2018, Comput. Educ..

Paving the way for providing teaching feedback in automatic evaluation of open response assignments

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Oscar Luaces, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option

José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Prediction and Inheritance of Phenotypes

José Ramón Quevedo, Juan José del Coz, Oscar Luaces, 2009, IWINAC.

Learning to Assess from Pair-Wise Comparisons

Juan José del Coz, Oscar Luaces, Jorge Díez, 2002, IBERAMIA.