A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman-Tversky’s prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown. Notably, a behavioral economist Prelec (1998) axioma...

Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles typically fall into instance-based, cluster-based, or hybrid approaches; however, most of such methods fail in discriminating among the various clusterings that participate to the ensemble. In this paper, we address th...

PURPOSE Energy-resolved CT has the potential to improve the contrast-to-noise ratio (CNR) through optimal weighting of photons detected in energy bins. In general, optimal weighting gives higher weight to the lower energy photons that contain the most contrast information. However, low-energy photons are generally most corrupted by scatter and spectrum tailing, an effect caused by the limited e...

Agents of general intelligence deployed in real-world scenarios must adapt to ever-changing environmental conditions. While such adaptive agents may leverage engineered knowledge, they will require the capacity to construct and evaluate knowledge themselves from their own experience in a bottom-up, constructivist fashion. This position paper builds on the idea of encoding knowledge as temporall...

In this paper a hierarchical classification framework using the feature-weighting tree for the objective of applying diverse weighting to acoustic features is proposed for speech recognition. The hierarchical feature-weighting tree with a flexible structure complexity can be constructed optimally with the optimal splitting for the recognition confusion graph. Based on the minimum classification...

Performance of an information retrieval system depends on its weighting scheme. Weighting of a term can be seen in two aspects, local and global. For each type of weighting scheme, generally, single terms are considered. Term dependency is quite natural in a document. Word pairs or phrases can better describe a document in place of single terms. In the present paper an attempt has been made to ...

Text Classification is one of the booming area in research with the availability of huge amount of electronic data in the form of news article, research articles, email message, blog, web pages etc. Text Representation is a vital step for text classification. In text representation, term weighting method assigns appropriate weights to the term to get better performance; the term weighting metho...

We present two approaches for the Euclidean TSP which compute high quality tours for large instances. Both approaches are based on pseudo backbones consisting of all common edges of good tours. The first approach starts with some pre-computed good tours. Using this approach we found record tours for seven VLSI instances. The second approach is window based and constructs from scratch very good ...