Now showing items 1-10 of 16
"Intelligente" læringssystemer: Fra leken Furby til spamfiltre til miljø
(Conference object; Konferansebidrag, 2010-09-02)
A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines
(Journal article; Tidsskriftartikkel; Peer reviewed, 2012)
We provide a novel interpretation of the dual of support vector machines (SVMs) in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. This enables us to implement computationally efficient ...
Consensus Clustering Using kNN Mode Seeking
(Chapter; Bokkapittel, 2015-06-09)
In this paper we present a novel clustering approach which combines two modern strategies, namely consensus clustering, and two stage clustering as represented by the mean shift spectral clustering algorithm. We introduce the recent kNN mode seeking algorithm in the consensus clustering framework, and the information theoretic kNN Cauchy Schwarz divergence as foundation for spectral clustering. In ...
Deep kernelized autoencoders
(Peer reviewed; Book; Bok; Bokkapittel; Chapter, 2017-05-19)
In this paper we introduce the deep kernelized autoencoder, a neural network model that allows an explicit approximation of (i) the mapping from an input space to an arbitrary, user-specified kernel space and (ii) the back-projection from such a kernel space to input space. The proposed method is based on traditional autoencoders and is trained through a new unsupervised loss function. ...
Using anchors from free text in electronic health records to diagnose postoperative delirium
(Journal article; Tidsskriftartikkel; Peer reviewed, 2017-09-19)
Objectives:<br> Postoperative delirium is a common complication after major surgery among the elderly. Despite its potentially serious consequences, the complication often goes undetected and undiagnosed. In order to provide diagnosis support one could potentially exploit the information hidden in free text documents from electronic health records usin ...
Multiplex visibility graphs to investigate recurrent neural network dynamics
(Journal article; Tidsskriftartikkel; Peer reviewed, 2017-03-10)
A recurrent neural network (RNN) is a universal approximator of dynamical systems, whose performance often depends on sensitive hyperparameters. Tuning them properly may be difficult and, typically, based on a trial-and-error approach. In this work, we adopt a graph-based framework to interpret and characterize internal dynamics of a class of RNNs called echo state networks (ESNs). We design principled ...
Spectral clustering using PCKID – A probabilistic cluster kernel for incomplete data
(Journal article; Manuskript; Tidsskriftartikkel; Peer reviewed; Preprint, 2017-05-19)
In this paper, we propose <i>PCKID</i>, a novel, robust, kernel function for spectral clustering, specifically designed to handle incomplete data. By combining posterior distributions of Gaussian Mixture Models for incomplete data on different scales, we are able to learn a kernel for incomplete data that does not depend on any critical hyperparameters, unlike the commonly used RBF kernel. To evaluate ...
Training Echo State Networks with Regularization Through Dimensionality Reduction
(Journal article; Tidsskriftartikkel; Peer reviewed, 2017)
In this paper, we introduce a new framework to train a class of recurrent neural network, called Echo State Network, to predict real valued time-series and to provide a visualization of the modeled system dynamics. The method consists in projecting the output of the internal layer of the network on a lower dimensional space, before training the output layer to learn the target task. Notably, we ...
Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2018-01-09)
To maintain the reliability, availability, and sustainability of electricity supply, electricity companies regularly perform visual inspections on their transmission and distribution networks. These inspections have been typically carried out using foot patrol and/or helicopter-assisted methods to plan for necessary repair or replacement works before any major damage, which may cause power outage. ...
Ranking Using Transition Probabilities Learned from Multi-Attribute Data
(Journal article; Tidsskriftartikkel; Peer reviewed, 2018-09-13)
In this paper, as a novel approach, we learn Markov chain transition probabilities for ranking of multi-attribute data from the inherent structures in the data itself. The procedure is inspired by consensus clustering and exploits a suitable form of the PageRank algorithm. This is very much in the spirit of the original PageRank utilizing the hyperlink structure to learn such probabilities. ...