In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
This paper presents an analysis of the design of classifiers for use in a hierarchical object recognition approach. In this approach, a cascade of classifiers is arranged in a tr...
Bjoern Stenger, Arasanathan Thayananthan, Philip H...
A new inductive learning system, Lab Learning for ABduction, is presented which acquires abductive rules from a set of training examples. The goal is to nd a small knowledge base ...
An astronomical set of sentences can be produced in natural language by combining relatively simple sentence structures with a human-size lexicon. These sentences are within the ra...
Frank van der Velde, Gwendid T. van der Voort van ...
This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...