We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
Ontology Learning from text aims at generating domain ontologies from textual resources by applying natural language processing and machine learning techniques. It is inherent in t...
A survey of niching algorithms, based on 5 variants of derandomized Evolution Strategies (ES), is introduced. This set of niching algorithms, ranging from the very first derandom...
Classification of email is an important everyday task for a large and growing number of users. This paper describes the machine learning approaches underlying the i-ems (Intellige...