Jorge Díez

Publication Activity (10 Years)

Years Active: 2002-2023
Publications (10 Years): 17

Top Topics

Recommender Systems

Preference Learning

Euclidean Space

Matrix Factorization

Top Venues

Prog. Artif. Intell.

Multim. Tools Appl.

Knowl. Based Syst.

Publications

Pablo Pérez-Núñez, Jorge Díez, Beatriz Remeseiro, Oscar Luaces, Antonio Bahamonde
All-in-one picture: visual summary of items in a recommender system. Neural Comput. Appl. 35 (27) (2023)
Pablo Pérez-Núñez, Jorge Díez, Oscar Luaces, Beatriz Remeseiro, Antonio Bahamonde
Users' photos of items can reveal their tastes in a recommender system. Inf. Sci. 642 (2023)
Pablo Pérez-Núñez, Jorge Díez, Oscar Luaces, Antonio Bahamonde
Correction to: User encoding for clustering in very sparse recommender systems tasks. Multim. Tools Appl. 81 (23) (2022)
Pablo Pérez-Núñez, Jorge Díez, Oscar Luaces, Antonio Bahamonde
User encoding for clustering in very sparse recommender systems tasks. Multim. Tools Appl. 81 (2) (2022)
Jorge Díez, Pablo Pérez-Núñez, Oscar Luaces, Beatriz Remeseiro, Antonio Bahamonde
Towards explainable personalized recommendations by learning from users' photos. Inf. Sci. 520 (2020)
Pablo Pérez-Núñez, Oscar Luaces, Antonio Bahamonde, Jorge Díez
Improving recommender systems by encoding items and user profiles considering the order in their consumption history. Prog. Artif. Intell. 9 (1) (2020)
Jorge Díez, David Martínez-Rego, Amparo Alonso-Betanzos, Oscar Luaces, Antonio Bahamonde
Optimizing novelty and diversity in recommendations. Prog. Artif. Intell. 8 (1) (2019)
Shu-Chao Pang, AnAn Du, Xiaoli He, Jorge Díez, Mehmet A. Orgun
Fast and Accurate Lung Tumor Spotting and Segmentation for Boundary Delineation on CT Slices in a Coarse-to-Fine Framework. ICONIP (4) (2019)
Oscar Luaces, Jorge Díez, Antonio Bahamonde
A peer assessment method to provide feedback, consistent grading and reduce students' burden in massive teaching settings. Comput. Educ. 126 (2018)
Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez
Deep Learning and Preference Learning for Object Tracking: A Combined Approach. Neural Process. Lett. 47 (3) (2018)
Jaime Alonso, Jorge Díez, Oscar Luaces, Antonio Bahamonde
A new method to learn growth curves of beef cattle using a factorization approach. Comput. Electron. Agric. 151 (2018)
Oscar Luaces, Jorge Díez, Amparo Alonso-Betanzos, Alicia Troncoso, Antonio Bahamonde
Content-based methods in peer assessment of open-response questions to grade students as authors and as graders. Knowl. Based Syst. 117 (2017)
Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez
Deep learning to frame objects for visual target tracking. Eng. Appl. Artif. Intell. 65 (2017)
Pablo González, Jorge Díez, Nitesh V. Chawla, Juan José del Coz
Why is quantification an interesting learning problem? Prog. Artif. Intell. 6 (1) (2017)
Verónica Bolón-Canedo, Jorge Díez, Oscar Luaces, Antonio Bahamonde, Amparo Alonso-Betanzos
Paving the way for providing teaching feedback in automatic evaluation of open response assignments. IJCNN (2017)
Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez
Combining Deep Learning and Preference Learning for Object Tracking. ICONIP (3) (2016)
Jorge Díez, Juan José del Coz, Oscar Luaces, Antonio Bahamonde
Using tensor products to detect unconditional label dependence in multilabel classifications. Inf. Sci. 329 (2016)
Jorge Díez, Oscar Luaces, Juan José del Coz, Antonio Bahamonde
Optimizing different loss functions in multilabel classifications. Prog. Artif. Intell. 3 (2) (2015)
Oscar Luaces, Jorge Díez, Thorsten Joachims, Antonio Bahamonde
Mapping preferences into Euclidean space. Expert Syst. Appl. 42 (22) (2015)
Oscar Luaces, Jorge Díez, Amparo Alonso-Betanzos, Alicia Troncoso, Antonio Bahamonde
Including Content-Based Methods in Peer-Assessment of Open-Response Questions. ICDM Workshops (2015)
Oscar Luaces, Jorge Díez, Amparo Alonso-Betanzos, Alicia Troncoso Lora, Antonio Bahamonde
A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments. Knowl. Based Syst. 85 (2015)
Jorge Díez, Edna Gamboa, Teresita González de Cossío, Oscar Luaces, Thorsten Joachims, Antonio Bahamonde
Analysis of nutrition data by means of a matrix factorization method. Prog. Artif. Intell. 3 (3-4) (2015)
José Barranquero, Jorge Díez, Juan José del Coz
Quantification-oriented learning based on reliable classifiers. Pattern Recognit. 48 (2) (2015)
José Barranquero, Pablo González, Jorge Díez, Juan José del Coz
On the study of nearest neighbor algorithms for prevalence estimation in binary problems. Pattern Recognit. 46 (2) (2013)
Elena Montañés, José Barranquero, Jorge Díez, Juan José del Coz
Enhancing directed binary trees for multi-class classification. Inf. Sci. 223 (2013)
Pablo González, Eva Alvarez, José Barranquero, Jorge Díez, Rafael Gonzalez-Quiros, Enrique Nogueira, Angel Lopez-Urrutia, Juan José del Coz
Multiclass Support Vector Machines With Example-Dependent Costs Applied to Plankton Biomass Estimation. IEEE Trans. Neural Networks Learn. Syst. 24 (11) (2013)
Oscar Luaces, Jorge Díez, José Barranquero, Juan José del Coz, Antonio Bahamonde
Binary relevance efficacy for multilabel classification. Prog. Artif. Intell. 1 (4) (2012)
Juan José del Coz, Jorge Díez, Antonio Bahamonde, Félix Goyache
Learning data structure from classes: A case study applied to population genetics. Inf. Sci. 193 (2012)
Oscar Luaces, José Ramón Quevedo, Miguel Pérez-Enciso, Jorge Díez, Juan José del Coz, Antonio Bahamonde
Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models. J. Comput. Biol. 17 (12) (2010)
Jorge Díez, Juan José del Coz, Antonio Bahamonde
A semi-dependent decomposition approach to learn hierarchical classifiers. Pattern Recognit. 43 (11) (2010)
Jorge Díez, Juan José del Coz, Antonio Bahamonde, Oscar Luaces
Soft Margin Trees. ECML/PKDD (1) (2009)
Antonio Bahamonde, Jaime Alonso, Juan José del Coz, Jorge Díez, José Ramón Quevedo, Oscar Luaces
Prediction and Inheritance of Phenotypes. IWINAC (1) (2009)
Juan José del Coz, Jorge Díez, Antonio Bahamonde
Learning Nondeterministic Classifiers. J. Mach. Learn. Res. 10 (2009)
Jaime Alonso, Juan José del Coz, Jorge Díez, Oscar Luaces, Antonio Bahamonde
Learning to Predict One or More Ranks in Ordinal Regression Tasks. ECML/PKDD (1) (2008)
Jorge Díez, Juan José del Coz, Oscar Luaces, Antonio Bahamonde
Clustering people according to their preference criteria. Expert Syst. Appl. 34 (2) (2008)
Juan José del Coz, Jorge Díez, Antonio Bahamonde, Carlos Sañudo, Matilde Alfonso, Philippe Berge, Eric Dransfield, Costas Stamataris, Demetrios Zygoyiannis, Tyri Valdimarsdottir, Edi Piasentier, Geoffrey Nute, Alan Fisher
Learning the Reasons Why Groups of Consumers Prefer Some Food Products. ICDM (2006)
Jorge Díez, Juan José del Coz, Carlos Sañudo, Pere Albertí, Antonio Bahamonde
A Kernel Based Method for Discovering Market Segments in Beef Meat. PKDD (2005)
Juan José del Coz, Gustavo F. Bayón, Jorge Díez, Oscar Luaces, Antonio Bahamonde, Carlos Sañudo
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM. NIPS (2004)
Jorge Díez, Gustavo F. Bayón, José Ramón Quevedo, Juan José del Coz, Oscar Luaces, Jaime Alonso, Antonio Bahamonde
Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis. ECAI (2004)
Oscar Luaces, Gustavo F. Bayón, José Ramón Quevedo, Jorge Díez, Juan José del Coz, Antonio Bahamonde
Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection. ECML (2004)
Antonio Bahamonde, Gustavo F. Bayón, Jorge Díez, José Ramón Quevedo, Oscar Luaces, Juan José del Coz, Jaime Alonso, Félix Goyache
Feature subset selection for learning preferences: a case study. ICML (2004)
Jorge Díez, Juan José del Coz, Oscar Luaces, Félix Goyache, Jaime Alonso, A. M. Peña, Antonio Bahamonde
Learning to Assess from Pair-Wise Comparisons. IBERAMIA (2002)