46 citations · 67 across the 8 of their papers we have counts for
5 papers · 1 filter
Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time series
Matthieu Herrmann, Chang Wei Tan, Mahsa Salehi +1
Time series classification (TSC) is a challenging task due to the diversity of types of feature that may be relevant for different classification tasks, including trends, variance,…
Parameterizing the cost function of Dynamic Time Warping with application to time series classification
Matthieu Herrmann, Chang Wei Tan, Geoffrey I. Webb
Dynamic Time Warping (DTW) is a popular time series distance measure that aligns the points in two series with one another. These alignments support warping of the time dimension t…
Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time Warping
Matthieu Herrmann, Geoffrey I. Webb
Dynamic Time Warping (DTW), and its constrained (CDTW) and weighted (WDTW) variants, are time series distances with a wide range of applications. They minimize the cost of non-line…
Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping
Matthieu Herrmann, Geoffrey I. Webb
Nearest neighbor search under elastic distances is a key tool for time series analysis, supporting many applications. However, straightforward implementations of distances require…
Early Abandoning PrunedDTW and its application to similarity search
Matthieu Herrmann, Geoffrey I. Webb
The Dynamic Time Warping ("DTW") distance is widely used in time series analysis, be it for classification, clustering or similarity search. However, its quadratic time complexity…