The Jaccard loss, commonly referred to as the intersection-over-union loss, is commonly employed in the evaluation of segmentation quality due to its better perceptual quality and scale invariance, which lends appropriate relevance to small objects compared with per-pixel losses. We present a method for direct optimization of the per-image intersection-over-union loss in neural networks, in the...

In today’s digital society, electronic information is increasingly shared among different entities, and decisions are made based on common attributes. To address associated privacy concerns, the research community has begun to develop cryptographic techniques for controlled (privacy-preserving) information sharing. One interesting open problem involves two mutually distrustful parties that need...

This paper proposes the implicative rating measure developed on the typicality measure. The paper also proposes a new recommendation model presenting the top N items to the active users. The proposed model is based on the user-based collaborative filtering approach using the implicative intensity measure to find the nearest neighbors of the active users, and the proposed measure to predict user...

Locating pairwise differences among treatment groups is a common practice of applied researchers. Articles published in this journal have addressed the issue of statistical inference within the context of an analysis of variance (ANOVA) framework, describing procedures for comparing means, among other issues. In particular, 1 article (Jaccard & Guilamo-Ramos, 2002b) presented some new methods o...

In this paper we present a hybrid approach based on combining fuzzy clustering, seed region growing, and Jaccard similarity coefficient algorithms to measure gray (GM) and white matter tissue (WM) volumes from magnetic resonance images (MRIs). The proposed algorithm incorporates intensity and anatomic information for segmenting of MRIs into different tissue classes, especially GM and WM. It sta...

Positive definite kernels are an important tool in machine learning that enable efficient solutions to otherwise difficult or intractable problems by implicitly linearizing the problem geometry. In this paper we develop a set-theoretic interpretation of the Earth Mover’s Distance (EMD) that naturally yields metric and kernel forms of EMD as generalizations of elementary set operations. In parti...

In social data analytics, Virtual Community (VC) detection is a primary challenge in discovering user relationships and enhancing recommendations. VC formation used for personal interaction between communities. But the usual methods didn’t find Suspicious Behaviour (SB) needed to make VC. The Generalized Jaccard Behavior Similarity-based Recurrent Deep Neural Network Classification Ranking (GJS...

The daily fluctuation trends of a stock market are illustrated by three statuses: up, equal, and down. These can be represented by a neutrosophic set which consists of three functions—truth-membership, indeterminacy-membership, and falsity-membership. In this paper, we propose a novel forecasting model based on neutrosophic set theory and the fuzzy logical relationships between the status of hi...

A common need in statistics is to assess whether two samples come from the same underlying population distribution. Existing two-sample tests often make limiting a priori assumptions, or cannot be easily generalized to multivariate data. We derive a new multivariate two-sample test that makes no a priori assumptions, has higher statistical power than previous tests, has better runtime performan...