Abstract--We investigate parameter-based and distributionbased approaches to regularizing the generative, similarity-based classifier called local similarity discriminant analysis ...
Traditional aspect graphs are topology-based and are impractical for articulated objects. In this work we learn a small number of aspects, or prototypical views, from video data. ...
Probability trees (or Probability Estimation Trees, PET’s) are decision trees with probability distributions in the leaves. Several alternative approaches for learning probabilit...
Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice...
— Most research in machine learning focuses on scenarios in which a learner faces a single learning task, independently of other learning tasks or prior knowledge. In reality, ho...
Abstract— Learning is an essential pruning technique in modern SAT solvers, but it exploits a relatively small amount of information that can be deduced from the conflicts. Rece...