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Found 10 papers, 0 papers with code
Semi-Metrification of the Dynamic Time Warping Distance
As a consequence, the dtw-distance is not warping-invariant, which in turn results in peculiarities in data mining applications.
Warped-Linear Models for Time Series Classification
This article proposes and studies warped-linear models for time series classification.
Optimal Warping Paths are unique for almost every Pair of Time Series
Update rules for learning in dynamic time warping spaces are based on optimal warping paths between parameter and input time series.
On the Existence of a Sample Mean in Dynamic Time Warping Spaces
The concept of sample mean in dynamic time warping (DTW) spaces has been successfully applied to improve pattern recognition systems and generalize centroid-based clustering algorithms.
Condorcet's Jury Theorem for Consensus Clustering and its Implications for Diversity
Condorcet's Jury Theorem has been invoked for ensemble classifiers to indicate that the combination of many classifiers can have better predictive performance than a single classifier.
The Mean Partition Theorem of Consensus Clustering
For this, we present the necessary condition of optimality in a slightly stronger form in terms of the Mean Partition Theorem and extend it to the Expected Partition Theorem.
Properties of the Sample Mean in Graph Spaces and the Majorize-Minimize-Mean Algorithm
One of the most fundamental concepts in statistics is the concept of sample mean.
Geometry of Graph Edit Distance Spaces
We derive a number of geometrical results from the orbit space representation, translate them to the graph space, and indicate their significance and usefulness in statistical pattern recognition.
Sublinear Models for Graphs
This contribution extends linear models for feature vectors to sublinear models for graphs and analyzes their properties.
