Exploració per autor "Tosi, Alessandra"
Ara es mostren els items 1-6 de 6
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Averaging of kernel functions
(2012)
Text en actes de congrés
Accés obertIn kernel-based machines, the integration of several kernels to build more flexible learning methods is a promising avenue for research. In particular, in Multiple Kernel Learning a compound kernel is build by learning a ... -
Cartogram representation of the batch-SOM magnification factor
(2012)
Text en actes de congrés
Accés restringit per política de l'editorialModel interpretability is a problem of knowledge extraction from the patterns found in raw data. One key source of knowledge is information visualization, which can help us to gain insights into a problem through graphical ... -
Metrics for probabilistic geometries
(AUAI Press (Association for Uncertainty in Artificial Intelligence), 2014)
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Accés restringit per política de l'editorialWe investigate the geometrical structure of probabilistic generative dimensionality reduction models using the tools of Riemannian geometry. We explicitly define a distribution over the natural metric given by the models. ... -
Probability ridges and distortion flows: Visualizing multivariate time series using a variational Bayesian manifold learning method
(Springer, 2014)
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Accés obertTime-dependent natural phenomena and artificial processes can often be quantitatively expressed as multivariate time series (MTS). As in any other process of knowledge extraction from data, the analyst can benefit from the ... -
Robust cartogram visualization of outliers in manifold learning
(2013)
Text en actes de congrés
Accés obertMost real data sets contain atypical observations, often referred to as outliers. Their presence may have a negative impact in data modeling using machine learning. This is particularly the case in data density estimation ... -
Visualization and interpretability in probabilistic dimensionality reduction models
(Universitat Politècnica de Catalunya, 2014-12-19)
Tesi
Accés obertOver the last few decades, data analysis has swiftly evolved from being a task addressed mainly within the remit of multivariate statistics, to an endevour in which data heterogeneity, complexity and even sheer size, driven ...
