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The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...
We cast the query by example spoken term detection (QbE-STD) problem as subspace detection where query and background subspaces are modeled as union of low-dimensional subspaces. The speech exemplars used for subspace modeling are class-conditional posteri ...
Idiap2016
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Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...
In this paper, we propose a novel algorithm for dimensionality reduction that uses as a criterion the mutual information (MI) between the transformed data and their cor- responding class labels. The MI is a powerful criterion that can be used as a proxy to ...
Institute of Electrical and Electronics Engineers2015
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As radio telescope data is now increasingly high-dimensional, data reduction has become essential to reduce computational load while preserving accurate signal reconstruction. Gridding the continuous Fourier visibilities represents the standard approach to ...
The amount of data that we produce and consume is larger than it has been at any point in the history of mankind, and it keeps growing exponentially. All this information, gathered in overwhelming volumes, often comes with two problematic characteristics: ...
The continuous increase, witnessed in the last decade, of both the amount of available data and the areas of application of machine learning, has lead to a demand for both learning and planning algorithms that are capable of handling large-scale problems. ...
This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of ma ...
The Web became the central medium for valuable sources of information extraction applications. However, such user-generated resources are often plagued by inaccuracies and misinformation due to the inherent openness and uncertainty of the Web. In this work ...
Many natural and man-made signals can be described as having a few degrees of freedom relative to their size due to natural parameterizations or constraints; examples include bandlimited signals, collections of signals observed from multiple viewpoints in ...
