Software process simulation models hold out the promise of improving project planning and control. However, purely quantitative models require a very detailed understanding of the software process, i.e. process knowledge represented quantitatively. When such data is lacking, quantitative models impose severe constraints, restricting the model’s value. In contrast, qualitative models display all...

800x600 normal 0 false false false en-us x-none ar-sa microsoftinternetexplorer4 background: this study’s aim was to design and validate a semi-quantitative food frequency questionnaire (ffq) for assessment of fruits and vegetables (fv) consumption in adults of isfahan by comparing the ffq with dietary reference method and blood plasma levels of beta-carotene, vitamin c, and retinol. methods: t...

Aiming at improving performance of visual classification in a cost-effective manner, this paper proposes an incremental semi-supervised learning paradigm called Deep CoSpace (DCS). Unlike many conventional semi-supervised learning methods usually performing within a fixed feature space, our DCS gradually propagates information from labeled samples to unlabeled ones along with deep feature learn...

We consider the task of learning a classifier from the feature space X to the set of classes Y = {0, 1}, when the features can be partitioned into class-conditionally independent feature sets X1 and X2. We show that the class-conditional independence can be used to represent the original learning task in terms of 1) learning a classifier from X2 to X1 (in the sense of estimating the probability...

This paper presents an unsupervised approach for dialogue act (DA) classification. We used a latent variable model to compress the dimensions of the feature vector. We introduced a paraphraser to reduce the variety of expressions and to solve the pragmatic problem for DA classification. The paraphraser seemed to work well on some DA classifications in the unsupervised approach. The results obta...