J. Díez

发表

Learning Nondeterministic Classifiers

Juan José del Coz, Jorge Díez, Antonio Bahamonde, 2009, J. Mach. Learn. Res..

Clustering of preference criteria

J. J. Coz, J. Díez, A. Bahamonde, 2003 .

Validation methods for plankton image classification systems

J. Díez, A. Lopez-Urrutia, Pablo González, 2017 .

Using machine learning procedures to ascertain the influence of beef carcass profiles on carcass conformation scores.

J. Díez, A. Bahamonde, G. Ripoll, 2006, Meat science.

Using pedigree information to monitor genetic variability of endangered populations: the Xalda sheep breed of Asturias as an example

J. Díez, F. Goyache, J. Gutiérrez, 2003 .

Characterization of Volatile Compounds in New Cider Apple Genotypes Using Multivariate Analysis

J. Díez, P. Abrodo, M. G. Alvarez, 2016, Food Analytical Methods.

Automatic plankton quantification using deep features

Juan José del Coz, Jorge Díez, Alberto Castaño, 2019, Journal of Plankton Research.

Genetic relationships between calving date, calving interval, age at first calving and type traits in beef cattle

J. Díez, F. Goyache, J. Gutiérrez, 2002 .

Optimizing different loss functions in multilabel classifications

J. J. Coz, J. Díez, A. Bahamonde, 2015, Progress in Artificial Intelligence.

Soft Margin Trees

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

Clustering people according to their preference criteria

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

G enetic relationships between calving date , calving interval , age at first calving and type traits in beef cattle

J. Díez, F. Goyache, J. Gutiérrez, 2002 .

Predicting fertility from seminal traits: Performance of several parametric and non-parametric procedures

Elena Montañés, José Ramón Quevedo, Jorge Díez, 2013 .

Identifying market segments in beef: Breed, slaughter weight and ageing time implications.

J. Díez, A. Bahamonde, B. Panea, 2006, Meat science.

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

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

Feature subset selection for learning preferences: a case study

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

User encoding for clustering in very sparse recommender systems tasks

J. Díez, A. Bahamonde, O. Luaces, 2021, Multimedia Tools and Applications.

Enhancing directed binary trees for multi-class classification

Elena Montañés, Juan José del Coz, José Barranquero, 2013, Inf. Sci..

Quantification-oriented learning based on reliable classifiers

Juan José del Coz, Jorge Díez, José Barranquero, 2015, Pattern Recognit..

Why is quantification an interesting learning problem?

Nitesh V. Chawla, Juan José del Coz, Jorge Díez, 2016, Progress in Artificial Intelligence.

On the study of nearest neighbor algorithms for prevalence estimation in binary problems

Juan José del Coz, Jorge Díez, Pablo González, 2013, Pattern Recognit..

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..

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

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

Mapping preferences into Euclidean space

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

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).

Binary relevance efficacy for multilabel classification

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

Deep learning to frame objects for visual target tracking

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

A semi-dependent decomposition approach to learn hierarchical classifiers

Juan José del Coz, Jorge Díez, Antonio Bahamonde, 2010, 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 .

Towards explainable personalized recommendations by learning from users' photos

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

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.

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..

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..

Learning data structure from classes: A case study applied to population genetics

Juan José del Coz, Jorge Díez, Antonio Bahamonde, 2012, Inf. Sci..

All-in-one picture: visual summary of items in a recommender system

J. Díez, A. Bahamonde, O. Luaces, 2023, Neural Computing and Applications.

Learning to Predict One or More Ranks in Ordinal Regression Tasks

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

Fast and Accurate Lung Tumor Spotting and Segmentation for Boundary Delineation on CT Slices in a Coarse-to-Fine Framework

Mehmet A. Orgun, Anan Du, Xiaoli He, 2019, ICONIP.

Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models

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

Prediction and Inheritance of Phenotypes

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

Users' photos of items can reveal their tastes in a recommender system

J. Díez, A. Bahamonde, O. Luaces, 2023, Inf. Sci..

Optimizing novelty and diversity in recommendations

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

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

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

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

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

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

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