18 citations · 35 across the 3 of their papers we have counts for
4 papers
Knowledge-Based Hierarchical POMDPs for Task Planning
Sergio A. Serrano, Elizabeth Santiago, Jose Martinez-Carranza +2
The main goal in task planning is to build a sequence of actions that takes an agent from an initial state to a goal state. In robotics, this is particularly difficult because acti…
Towards AutoML in the presence of Drift: first results
Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales +5
Research progress in AutoML has lead to state of the art solutions that can cope quite wellwith supervised learning task, e.g., classification with AutoSklearn. However, so far the…
Meta-learning of textual representations
Jorge Madrid, Hugo Jair Escalante, Eduardo Morales
Recent progress in AutoML has lead to state-of-the-art methods (e.g., AutoSKLearn) that can be readily used by non-experts to approach any supervised learning problem. Whereas thes…
Term-Weighting Learning via Genetic Programming for Text Classification
Hugo Jair Escalante, Mauricio A. García-Limón, Alicia Morales-Reyes +3
This paper describes a novel approach to learning term-weighting schemes (TWSs) in the context of text classification. In text mining a TWS determines the way in which documents wi…