The analysis of human activity data is an important research area in the context of ubiquitous and social environments. Using sensor data obtained by mobile devices, e. g., utilizi...
Martin Atzmueller, Mark Kibanov, Naveed Hayat, Mat...
Random walk with restart (RWR) is widely recognized as one of the most important node proximity measures for graphs, as it captures the holistic graph structure and is robust to no...
An important problem in multi-label classification is to capture label patterns or underlying structures that have an impact on such patterns. One way of learning underlying struc...
We present a Bayesian non-negative tensor factorization model for count-valued tensor data, and develop scalable inference algorithms (both batch and online) for dealing with massi...
Changwei Hu, Piyush Rai, Changyou Chen, Matthew Ha...
In this paper we describe a method to reuse models with Model-Based Subgroup Discovery (MBSD), which is a extension of the Subgroup Discovery scheme. The task is to predict the num...
Unlike conventional clustering, fuzzy cluster analysis allows data elements to belong to more than one cluster by assigning membership degrees of each data to clusters. This work p...
With the extensive amount of textual data flowing through social media platforms, the interest in Information Extraction (IE) on such textual data has increased. Named Entity Reco...
Abstract. Semi-supervised clustering algorithms allow the user to incorporate background knowledge into the clustering process. Often, this background knowledge is specified in th...
Abstract. Matrix factorization (MF) is the simplest and most well studied factor based model and has been applied successfully in several domains. One of the standard ways to solve...
Abstract. Learning problems in which an adversary can perturb instances at application time can be modeled as games with datadependent cost functions. In an equilibrium point, the ...