Publicaties
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The power of using continuous-wave and pulsed electron paramagnetic resonance methods for the structure analysis of ferric forms and nitric oxide-ligated ferrous forms of globins Universiteit Antwerpen
Supervised distance metric learning for pattern recognition Universiteit Gent
Much like in other modeling disciplines does the distance metric used (a measure for dissimilarity) play an important role in the growing field of machine learning. Often, predefined distance metrics (e.g. the Euclidean one) are used to perform such measurement. Unfortunately, most of them ignore any statistical properties that might be estimated from the data. The notion of a good distance metric changes when one moves from one domain to ...
Hardy inequalities on metric measure spaces : II. The case p>q Universiteit Gent
In this paper, we continue our investigations giving the characterization of weights for two-weight Hardy inequalities to hold on general metric measure spaces possessing polar decompositions. Since there may be no differentiable structure on such spaces, the inequalities are given in the integral form in the spirit of Hardy's original inequality. This is a continuation of our paper (Ruzhansky & Verma 2018. Proc. R. Soc. A 475, 20180310 ...
Class-specific discriminative metric learning for scene recognition Universiteit Gent
Scalable large-margin distance metric learning using stochastic gradient descent Universiteit Gent
The key to success of many machine learning and pattern recognition algorithms is the way of computing distances between the input data. In this paper, we propose a large-margin-based approach, called the large-margin distance metric learning (LMDML), for learning a Mahalanobis distance metric. LMDML employs the principle of margin maximization to learn the distance metric with the goal of improving k-nearest-neighbor classification. The main ...
An adjusted weight metric to quantify flexibility available in conventional generators for low carbon power systems Universiteit Gent
With the increasing shares of intermittent renewable sources in the grid, it becomes increasingly essential to quantify the requirements of the power systems flexibility. In this article, an adjusted weight flexibility metric (AWFM) is developed to quantify the available flexibility within individual generators as well as within the overall system. The developed metric is useful for power system operators who require a fast, simple, and offline ...
Stable topological signatures for metric trees through graph approximations Universiteit Gent
The rising field of Topological Data Analysis (TDA) provides a new approach to learning from data through persistence diagrams, which are topological signatures that quantify topological properties of data in a comparable manner. For point clouds, these diagrams are often derived from the Vietoris-Rips filtration—based on the metric equipped on the data—which allows one to deduce topological patterns such as components and cycles of the ...
An alternative approach to the median of a random interval using an L² metric Universiteit Gent
Since the Aumann-type expected value of a random interval is not robust, the aim of this paper is to propose a new central tendency measure for interval-valued data. The median of a random interval has already been defined as the interval minimizing the mean distance, in terms of an L-1 metric extending the Euclidean distance, to the values of the random interval. Inspired by the spatial median, we now follow a more common approach to define the ...