In this paper we propose a unified action recognition framework fusing local descriptors and
holistic features. The motivation is that the local descriptors and holistic features emphasize …

Android and Facebook provide third-party applications with access to users' private data and
the ability to perform potentially sensitive operations (eg, post to a user's wall or place phone …

The graduate admissions process is crucial for controlling the quality of higher education,
yet, rules-of-thumb and domain-specific experiences often dominate evidence-based …

Matrix factorizations—where a given data matrix is approximated by a product of two or more
factor matrices—are powerful data mining tools. Among other tasks, matrix factorizations are …

We propose a probabilistic model for clustering Boolean data where an object can be
simultaneously assigned to multiple clusters. By explicitly modeling the underlying …

Role mining tackles the problem of finding a role-based access control (RBAC)
configuration, given an access-control matrix assigning users to access permissions as …

Truncated Singular Value Decomposition (SVD) calculates the closest rank-k approximation
of a given input matrix. Selecting the appropriate rank k defines a critical model order choice …

Several clustering methods (eg, Normalized Cut and Ratio Cut) divide the Min Cut cost
function by a cluster dependent factor (eg, the size or the degree of the clusters), in order to …

During the last 20 years, predictive modeling in epilepsy research has largely been
concerned with the prediction of seizure events, whereas the inference of effective brain …

Quantitative structure–activity relationships are regression models relating chemical
structure to biological activity. Such models allow to make predictions for toxicologically …