Robust regression and outlier detection
Robust regression and outlier detection
Robust Clustering with Applications in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using consensus sequence voting to correct OCR errors
Computer Vision and Image Understanding
On a relation between graph edit distance and maximum common subgraph
Pattern Recognition Letters
A Spectral Algorithm for Seriation and the Consecutive Ones Problem
SIAM Journal on Computing
The String-to-String Correction Problem
Journal of the ACM (JACM)
Topology of strings: median string is NP-complete
Theoretical Computer Science
On Median Graphs: Properties, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Weighted mean of a pair of graphs
Computing
Computation of Normalized Edit Distance and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
A mean string algorithm to compute the average among a set of 2D shapes
Pattern Recognition Letters
Learning Metrics Between Tree Structured Data: Application to Image Recognition
ECML '07 Proceedings of the 18th European conference on Machine Learning
A symbol spotting approach in graphical documents by hashing serialized graphs
Pattern Recognition
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We introduce in this paper the concept of set deviation as a tool to characterize the deviation of a set of strings around its set median. The set deviation is defined as the set median of the positive edit sequences between any string and the set median. We show how the set deviation can be efficiently used in well known statistical estimation and particularly with the minimum volume ellipsoid estimator. This concept is illustrated on several examples and particularly in clustering a set of shapes coded as strings using the Freeman code.