Most of the previous research on term weighting for information retrieval has focused on developing specialized parametric term weighting functions. Examples include TF.IDF vector-space formulations, BM25, and language modeling weighting. Each of these term weighting functions takes on a specific parametric form. While these weighting functions have proven to be highly effective, they impose st...

This paper is a principal idea of case-based reasoning to feature weighting. The feature weighting method called CaDFeW (CAse-based Dynamic FEature Weighting) stores classification performance of randomly generated feature weight vectors. Also it retrieve similar feature weighting success story from the feature weighting case base and then designs a better feature weight vector dynamically for ...

Figure 1 shows the comparison of a general normal based weighting function and the proposed weighting function. They are rendered with voxel cone tracing [Crassin et al. 2011] and spatio-temporal upsampling [Herzog et al. 2010]. The scene has a dynamic object (a galloping horse). In this experiment, the normal based weighting function has a Gaussian distribution [Yang et al. 2008] and its varia...

ion in weighting tasks may allow for earlier application of the multiplicative rule. Schlottmann and Christoferou (in preparation) tested this possibility by giving fourto tenyear-olds a conjunctive area task and two weighting tasks, an EV task and a novel sourcemessage task. As predicted, the younger children multiplied in both weighting tasks, but added in the area task, supporting the view t...

Sensory-motor integration has frequently been studied using a single-step change in a control variable such as prismatic lens angle and has revealed human visuomotor adaptation to often be partial and inefficient. We propose that the changes occurring in everyday life are better represented as the accumulation of many smaller perturbations contaminated by measurement noise. We have therefore te...

Rare variant association studies are gaining importance in human genetic research with the increasing availability of exome/genome sequence data. One important test of association between a target set of rare variants (RVs) and a given phenotype is the sequence kernel association test (SKAT). Assignment of weights reflecting the hypothesized contribution of the RVs to the trait variance is embe...

this paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. the classification performance andinterpretability are of major importance in these systems. in this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). ourapproach uses a punish...

We consider the problem of assigning weights to a set samples or data records, with goal achieving representative weighting, which happens when certain sample averages are close prescribed values. frame finding as an optimization problem, in many cases is convex and can be efficiently solved. Our formulation includes special case selection fixed number samples, equal weights, i.e., selecting sm...