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  1. No Access

    Chapter and Conference Paper

    Robust Second-Order Source Separation Identifies Experimental Responses in Biomedical Imaging

    Multidimensional biomedical imaging requires robust statistical analyses. Corresponding experiments such as EEG or FRAP commonly result in multiple time series. These data are classically characterized by reco...

    Fabian J. Theis, Nikola S. Müller in Latent Variable Analysis and Signal Separa… (2010)

  2. No Access

    Chapter and Conference Paper

    Integrative Parameter-Free Clustering of Data with Mixed Type Attributes

    Integrative mining of heterogeneous data is one of the major challenges for data mining in the next decade. We address the problem of integrative clustering of data with mixed type attributes. Most existing so...

    Christian Böhm, Sebastian Goebl in Advances in Knowledge Discovery and Data M… (2010)

  3. No Access

    Chapter and Conference Paper

    Information-Theoretic Model Selection for Independent Components

    Independent Component Analysis (ICA) is an essential building block for data analysis in many applications. Selecting the truly meaningful components from the result of an ICA algorithm, or comparing the resul...

    Claudia Plant, Fabian J. Theis in Latent Variable Analysis and Signal Separa… (2010)

  4. No Access

    Chapter and Conference Paper

    SkyDist: Data Mining on Skyline Objects

    The skyline operator is a well established database primitive which is traditionally applied in a way that only a single skyline is computed. In this paper we use multiple skylines themselves as objects for da...

    Christian Böhm, Annahita Oswald in Advances in Knowledge Discovery and Data M… (2010)

  5. Chapter and Conference Paper

    ITCH: Information-Theoretic Cluster Hierarchies

    Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hierarchical clustering, we have i...

    Christian Böhm, Frank Fiedler in Machine Learning and Knowledge Discovery i… (2010)

  6. Chapter and Conference Paper

    Synchronization Based Outlier Detection

    The study of extraordinary observations is of great interest in a large variety of applications, such as criminal activities detection, athlete performance analysis, and rare events or exceptions identificatio...

    Junming Shao, Christian Böhm, Qinli Yang in Machine Learning and Knowledge Discovery i… (2010)

  7. No Access

    Chapter and Conference Paper

    Combining DTI and MRI for the Automated Detection of Alzheimer’s Disease Using a Large European Multicenter Dataset

    Diffusion tensor imaging (DTI) allows assessing neuronal fiber tract integrity in vivo to support the diagnosis of Alzheimer’s disease (AD). It is an open research question to which extent combinations of diff...

    Martin Dyrba, Michael Ewers, Martin Wegrzyn in Multimodal Brain Image Analysis (2012)

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    Chapter and Conference Paper

    Robust Synchronization-Based Graph Clustering

    Complex graph data now arises in various fields like social networks, protein-protein interaction networks, ecosystems, etc. To reveal the underlying patterns in graphs, an important task is to partition them ...

    Junming Shao, **ao He, Qinli Yang in Advances in Knowledge Discovery and Data M… (2013)

  9. No Access

    Chapter and Conference Paper

    Mining Medical Data to Obtain Fuzzy Predicates

    The collection of methods known as ‘data mining’ offers methodological and technical solutions to deal with the analysis of medical data and the construction of models. Medical data have a special status based...

    Taymi Ceruto, Orenia Lapeira, Annika Tonch in Information Technology in Bio- and Medical… (2014)

  10. No Access

    Chapter and Conference Paper

    Centroid Clustering of Cellular Lineage Trees

    Trees representing hierarchical knowledge are prevalent in biology and medicine. Some examples are phylogenetic trees, the hierarchical structure of biological tissues and cell lines. The increasing throughput...

    Valeriy Khakhutskyy, Michael Schwarzfischer in Information Technology in Bio- and Medical… (2014)

  11. No Access

    Chapter and Conference Paper

    Segmentation and Kinetic Analysis of Breast Lesions in DCE-MR Imaging Using ICA

    Dynamic Contrast Enhance-Magnetic Resonance Imaging (DCE-MRI) has proved to be a useful tool for diagnosing mass-like breast cancer. For non-mass-like lesions, however, no methods applied on DCE-MRI have shown...

    Sebastian Goebl, Anke Meyer-Baese in Information Technology in Bio- and Medical… (2014)

  12. No Access

    Chapter and Conference Paper

    Covariate-Related Structure Extraction from Paired Data

    In the biological domain, it is more and more common to apply several high-throughput technologies to the same set of samples. We propose a Covariate-Related Structure Extraction approach (CRSE) that explores ...

    Linfei Zhou, Elisabeth Georgii in Information Technology in Bio- and Medical… (2016)

  13. No Access

    Chapter and Conference Paper

    Stroke Lesion Segmentation Using a Probabilistic Atlas of Cerebral Vascular Territories

    The accurate segmentation of lesions in magnetic resonance images of stroke patients is important, for example, for comparing the location of the lesion with functional areas and for determining the optimal st...

    Alexandra Derntl, Claudia Plant in Brainlesion: Glioma, Multiple Sclerosis, S… (2016)

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    Chapter and Conference Paper

    Information-Theoretic Non-redundant Subspace Clustering

    A comprehensive understanding of complex data requires multiple different views. Subspace clustering methods open up multiple interesting views since they support data objects to be assigned to different clust...

    Nina Hubig, Claudia Plant in Advances in Knowledge Discovery and Data Mining (2017)

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    Chapter and Conference Paper

    Novel Indexing Strategy and Similarity Measures for Gaussian Mixture Models

    Efficient similarity search for data with complex structures is a challenging task in many modern data mining applications, such as image retrieval, speaker recognition and stock market analysis. A common way ...

    Linfei Zhou, Wei Ye, Bianca Wackersreuther in Database and Expert Systems Applications (2017)

  16. No Access

    Chapter and Conference Paper

    Knowledge Discovery of Complex Data Using Gaussian Mixture Models

    With the explosive growth of data quantity and variety, the representation and analysis of complex data becomes a more and more challenging task in many modern applications. As a general class of probabilistic...

    Linfei Zhou, Wei Ye, Claudia Plant in Big Data Analytics and Knowledge Discovery (2017)

  17. Chapter and Conference Paper

    Attributed Graph Clustering with Unimodal Normalized Cut

    Graph vertices are often associated with attributes. For example, in addition to their connection relations, people in friendship networks have personal attributes, such as interests, age, and residence. Such ...

    Wei Ye, Linfei Zhou, **n Sun, Claudia Plant in Machine Learning and Knowledge Discovery i… (2017)

  18. No Access

    Chapter and Conference Paper

    Indexing Multiple-Instance Objects

    As an actively investigated topic in machine learning, Multiple-Instance Learning (MIL) has many proposed solutions, including supervised and unsupervised methods. We introduce an indexing technique supporting...

    Linfei Zhou, Wei Ye, Zhen Wang, Claudia Plant in Database and Expert Systems Applications (2017)

  19. No Access

    Chapter and Conference Paper

    KMN - Removing Noise from K-Means Clustering Results

    K-Means is one of the most important data mining techniques for scientists who want to analyze their data. But K-Means has the disadvantage that it is unable to handle noise data points. This paper proposes a ...

    Benjamin Schelling, Claudia Plant in Big Data Analytics and Knowledge Discovery (2018)

  20. No Access

    Chapter and Conference Paper

    Parameter Free Mixed-Type Density-Based Clustering

    Nowadays many applications generate mixed data objects consisting of numerical and categorical attributes. Simultaneously dealing with mixed objects is more challenging and various approaches convert one type ...

    Sahar Behzadi, Mahmoud Abdelmottaleb Ibrahim in Database and Expert Systems Applications (2018)

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