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Adapting statistical learning models online with large scale streaming data is a challenging problem. Bayesian non-parametric mixture models provide flexibility in model selection, however, their widespread use is limited by the computational overhead of e ...
The identification and selection of a small set of models that are able to well describe and predict the error signals coming from IMU sensors is of utmost importance to improve the navigation precision of these devices. For this reason, in this paper we p ...
The application of systematic methodologies for the optimal design of integrated processes has seen increased interest in literature, namely for bioprocesses. The development and application of such a methodology to ethanol and power production from sugarc ...
The extraction of student behavior is an important task in educational data mining. A common approach to detect similar behavior patterns is to cluster sequential data. Standard approaches identify clusters at each time step separately and typically show l ...
The R package bclust is useful for clustering high-dimensional continuous data. The package uses a parametric spike-and-slab Bayesian model to downweight the effect of noise variables and to quantify the importance of each variable in agglomerative cluster ...
Networked computing environments are subject to configuration errors, unauthorized users, undesired activities and attacks by malicious software. These can be detected by monitoring network traffic, but network administrators are overwhelmed by the amount ...
Within the HMM state mapping-based cross-lingual speaker adaptation framework, the minimum Kullback-Leibler divergence criterion has been typically employed to measure the similarity of two average voice state distributions from two respective languages fo ...
In this paper, a new framework to discover places-of-interest from multimodal mobile phone data is presented. Mobile phones have been used as sensors to obtain location information from users’ real lives. A place-of-interest is defined as a location where ...
In this letter, an unsupervised kernel-based approach to change detection is introduced. Nonlinear clustering is utilized to partition in two a selected subset of pixels representing both changed and unchanged areas. Once the optimal clustering is obtained ...
A statistical shape model is a suitable tool for high accuracy eye modeling required for treatment planning for external beam radiotherapy of intraocular tumors. In this study, the automatically adapted eye model has been compared to manual segmentation ba ...
