A new method to pre-segment images by means of a hierarchical description is proposed. This description is obtained from an investigation of the deep structure of a scale space image – the input image and the Gaussian filtered ones simultaneously. We concentrate on scale space critical points – points with vanishing gradient with respect to both spatial and scale direction. We show that these p...

Introduction Instruments Prior knowledge tests Research intruments Subjects Results Discussion and conclusion References Abstract Many investigations have shown that prior knowledge state is one of the most determining factors and an important predictor of subsequent study outcomes. This research focuses on the evaluation of a set of electronic instruments to make potential students more aware ...

In 6 experiments, the authors examined the use of prior knowledge in category learning. Previous studies of the effects of knowledge on category learning have used categories in which knowledge was related to all of the category's features. However, people's knowledge of real-world categories often consists of many "rote" features that are not related to their prior knowledge. Five experiments ...

Developing general purpose algorithms for learning an accurate model of dynamical systems from example traces of the system is still a challenging research problem. Predictive State Representation (PSR) models represent the state of a dynamical system as a set of predictions about future events. Our work focuses on improving Temporal Difference Networks (TD Nets), a general class of predictive ...

When searching a tree to find the best leaf, complete search methods uch as depth-first search and depth-bounded discrepancy search use a fixed deterministic order that may or may not be appropriate for the tree at hand. Adaptive probing is a recently-proposed stochastic method that attempts to adjust its sampling on-line to focus on areas of the tree that seem to contain good solutions. While ...

Encoding knowledge is time consuming and expensive. A possible solution to reduce the cost of developing a new knowledge base (KB) is to reuse existing knowledge. Previous work addressing this problem has focused on standards for representing, exchanging, and accessing knowledge (Genesereth and Fikes 1992), (Chaudhri et al. 1998), and on creating large repositories of knowledge (Lenat and Guha ...

This paper presents a method to incorporate knowledge from possibly imperfect models and domain theories into inductive learning of decision trees for classification The approach assumes that a model or domain theory reflects useful prior knowledge of th< task Thus the default bias should accept the model s predictions as accurate even in the face of somewhat contradictory data which may be unr...

We address the task of automatic discovery of information extraction template from a given text collection. Our approach clusters candidate slot fillers to identify meaningful template slots. We propose a generative model that incorporates distributional prior knowledge to help distribute candidates in a document into appropriate slots. Empirical results suggest that the proposed prior can brin...

We report three experiments that explore the effect of prior linguistic knowledge on implicit language learning. Native speakers of English and native speakers of Cantonese participated in implicit learning (IL) experiments that involved different learning materials. In Experiment 1, both participant groups showed evidence of learning a mapping between articles and noun animacy. In Experiment 2...

Prior knowledge is an important factor that influences the interaction with a hypertext and the learning gain. Our authoring system NetCoach provides a way to assess the users’ prior knowledge and to adapt the course in different ways. We describe how the adaptation mechanism assesses the user’s knowledge with test items, infers the user’s current learning state from this information, and final...