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Finding Co-Clusters of Genes and Clinical Parameters

Publications associées (34)

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Computational Methods For Structured Sparse Component Analysis of Convolutive Speech Mixtures

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei

We cast the under-determined convolutive speech separation as sparse approximation of the spatial spectra of the mixing sources. In this framework we compare and contrast the major practical algorithms for structured sparse recovery of speech signal. Speci ...

2012

Computational Methods For Structured Sparse Component Analysis of Convolutive Speech Mixtures

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei

2012

Subspaces Indexing Model on Grassmann Manifold for Image Search

Xinchao Wang

Conventional linear subspace learning methods like principal component analysis (PCA), linear discriminant analysis (LDA) derive subspaces from the whole data set. These approaches have limitations in the sense that they are linear while the data distribut ...

Institute of Electrical and Electronics Engineers2011

Finding Audio-Visual Events in Informal Social Gatherings

In this paper we address the problem of detecting and localizing objects that can be both seen and heard, e.g., people. This may be solved within the framework of data clustering. We propose a new multimodal clustering algorithm based on a Gaussian mixture ...

2011

Low-rank tensor Krylov subspace methods for parametrized linear systems

Daniel Kressner, Christine Tobler

We consider linear systems A(alpha)x(alpha) - b(alpha) depending on possibly many parameters alpha = (alpha(1), ... , alpha(p)). Solving these systems simultaneously for a standard discretization of the parameter range would require a computational effort ...

Society for Industrial and Applied Mathematics2011

How much does it cost? Optimization of costs in sequence analysis of social science data

Philipp Bucher

One major methodological problem in analysis of sequence data is the determination of costs from which distances between sequences are derived. Although this problem is currently not optimally dealt with in the social sciences, it has some similarity with ...

SAGE Publications2009

Joint co-clustering: Co-clustering of genomic and clinical bioimaging data

Giovanni De Micheli, Luca Benini

For better understanding the genetic mechanisms underlying clinical observations, and better defining a group of potential candidates for protein-family-inhibiting therapy, it is interesting to determine the correlations between genomic, clinical data and ...

Elsevier2008

Computational Probability for Systems Biology

Stochastic models of biological networks properly take the randomness of molecular dynamics in living cells into account. Numerical solution approaches inspired by computational methods from applied probability can efficiently yield accurate results and ha ...

Springer2008

Clustering protein environments for function prediction: finding PROSITE motifs in 3D

Giovanni De Micheli

Background: Structural genomics initiatives are producing increasing numbers of three-dimensional (3D) structures for which there is little functional information. Structure-based annotation of molecular function is therefore becoming critical. We previous ...

BioMed Central2007

Bioimaging and Functional Genomics

Giovanni De Micheli, Luca Benini

For better understanding of genetic mechanisms underlying clinical observations, it is interesting to determine which genes and clinical traits are interrelated. In the last few years a consistent amount of research in genomics has been done concerning cor ...

2006