Aurora Esteban (started 2020) - Outiliers detection from an active learning perspective
Zaid Zubair (started 2020) - New Challenges in the development of reusable machine learning models
Antonio R. Moya (started 2020) - Improving the architecture and interpretability of Deep Neural Networks: an evolutionary computing approach.
Roula Khafaji (started 2020) - Improving Predictive Analysis with Longitudinal Data using Deep Learning Models
Ghaidaa Ali (started 2020) - Graph Representation by Using Machine Learning
Yaser M. Alasady (started 2020) - Design of an intelligent system for detection, identification, monitoring, forecasting and controlling of tomato pest Tuta Absoluta by using deep learning algorithms
Mustafa A. Shafeea (started 2020) - Deep Learning Models with Multiple Instance Data
Paolo Cachi (started 2019) - New spiking neural network models for incremental learning applied to image classification and object recognition problems
Mohammed Yahya (started 2019) - New Deep Learning Approaches in Anomaly Detection. Applications
Juan A. Marín (started 2019) - New Advances in Sequential Pattern Mining
Mohammed Al-Twijri (started 2019) - Mode lling Course Difficulty Indexes to Enhance Students Performance and Course Study Plans
Eduardo Perez (started 2018) - Automatic Diagnosis of Melanoma with Modern Machine Learning Techniques
Hermes Robles (started 2016) - New Clustering Methods Based on Evolutionary Computation
José Antonio Delgado (started 2016) - New Machine Learning Methods in Biomedicine
Francisco Padillo (2020) - New Challenges in Associative Classification: Big Data and Applications
Carmen Luque-Guzman (2020) - Text Mining y Medicina: Una Aproximación a la Detección Temprana de Enfermedades
José María Moyano (2020) - Multi-label Classification Models for Heterogeneous Data: an Ensemble-Based Approach
Jorge Gonzalez-Lopez (2019) - Distributed Multi-Label Learning on Apache Spark
Gabriella Melki (2018) - Novel Support Vector Machines for Diverse Learning Paradigms
Aurora Ramírez (2018) - Metaheuristic models to the development of decision support systems in software construction
Óscar G. Reyes (2016) - New hybrid learning models for multi-label classification and label ranking
Carlos Marquez-Vera (2015) - Prediction of Student Dropout by Data Mining Techniques
Alberto Cano (2014) - New Classification Models Based on Evolutionary Algorithms
José M. Luna (2014) - New challenges in association rule mining: An approach based on genetic programming
José Luis Ávila (2013) - New Genetic Programming Methods for Multi-label Classification
Juan Luis Olmo (2013) - Ant-Based Programming in Classification: Applications
Amelia Zafra (2009) - Grammar-Based Genetic Programming for Multiple Instance Learning
Cristobal Romero (2003) - Applying Knowledge Discovery Techniques for the Improvement of Web-Based Hipermedia Adaptive Courses