Projects per year
Abstract
This thesis presents a collection of statistical models that attempt to take advantage
of every piece of prior knowledge available to provide the models with as
much structure as possible. The main motivation for introducing these models
is interpretability since in practice we want to be able to use them as hypothesis
generating tools. All of our models start from a family of structures, for
instance factor models, directed acyclic graphs, classifiers, etc. Then we let
them be selectively sparse as a way to provide them with structural fl
exibility
and interpretability. Finally, we complement them with different prior assumptions
in order to make them appropriate at handling different domain specific
situations as time series, non-linearities, batch effects, missing values, etc. In
particular, we present a framework for linear Bayesian networks we call sparse
identifiable multivariate modeling, a model for peptide-protein/protein-protein
interactions called latent protein tree, a framework for sparse Gaussian process
classification based on active set selection and a linear multi-category sparse
classifier specially targeted to gene expression data. The thesis is organized to
provide a general yet self-contained description of every model in terms of generative
assumptions, interpretability goals, probabilistic formulation and target
applications. Case studies, benchmark results and practical details are also provided
as appendices published elsewhere, containing reprints of peer reviewed
material.
Original language | English |
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Place of Publication | Kgs. Lyngby, Denmark |
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Publisher | Technical University of Denmark |
Publication status | Published - 2011 |
Series | IMM-PHD-2011-253 |
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Fingerprint
Dive into the research topics of 'Sparse Multivariate Modeling: Priors and Applications'. Together they form a unique fingerprint.Projects
- 1 Finished
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Machine Learning for Integrating Biological Data Across Experimental Technologies
Henao, R. (PhD Student), Winther, O. (Main Supervisor), Hansen, L. K. (Examiner), Girolami, M. (Examiner) & Vehtari, A. (Examiner)
Technical University of Denmark
15/02/2008 → 01/06/2011
Project: PhD