This paper presents ACE (Autonomous Classification Engine), a framework for using and optimizing classifiers. Given a set of feature vectors, ACE experiments with a variety of cla...
Cory McKay, Rebecca Fiebrink, Daniel McEnnis, Bein...
For many large-scale combinatorial search/optimization problems, meta-heuristic algorithms face noisy objective functions, coupled with computationally expensive evaluation times....
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Video-rate registered range and intensity data are at reach of current sensor technology. This wealth of data can be pro tably exploited in order to estimate rigid motion paramete...
Luca Lucchese, Gianfranco Doretto, Guido M. Cortel...