10 citations · 24 across the 6 of their papers we have counts for
4 papers · 1 filter
Evolving Gaussian Process kernels from elementary mathematical expressions
Ibai Roman, Roberto Santana, Alexander Mendiburu +1
Choosing the most adequate kernel is crucial in many Machine Learning applications. Gaussian Process is a state-of-the-art technique for regression and classification that heavily…
Towards automatic construction of multi-network models for heterogeneous multi-task learning
Unai Garciarena, Alexander Mendiburu, Roberto Santana
Multi-task learning, as it is understood nowadays, consists of using one single model to carry out several similar tasks. From classifying hand-written characters of different alph…
Towards a more efficient representation of imputation operators in TPOT
Unai Garciarena, Alexander Mendiburu, Roberto Santana
Automated Machine Learning encompasses a set of meta-algorithms intended to design and apply machine learning techniques (e.g., model selection, hyperparameter tuning, model assess…
Evolving imputation strategies for missing data in classification problems with TPOT
Unai Garciarena, Roberto Santana, Alexander Mendiburu
Missing data has a ubiquitous presence in real-life applications of machine learning techniques. Imputation methods are algorithms conceived for restoring missing values in the dat…