Kernel-based generalized median computation for consensus learning
A Nienkötter, X Jiang - IEEE Transactions on Pattern Analysis …, 2022 - ieeexplore.ieee.org
Computing a consensus object from a set of given objects is a core problem in machine
learning and pattern recognition. One popular approach is to formulate it as an optimization …
learning and pattern recognition. One popular approach is to formulate it as an optimization …
[HTML][HTML] Hardness results for the center and median string problems under the weighted and unweighted edit distances
F Nicolas, E Rivals - Journal of discrete algorithms, 2005 - Elsevier
Given a finite set of strings, the Median String problem consists in finding a string that
minimizes the sum of the edit distances to the strings in the set. Approximations of the …
minimizes the sum of the edit distances to the strings in the set. Approximations of the …
Median strings: A review
Time series can be effectively represented by strings. The median concept is useful in
various contexts. In this chapter its adaptation to the domain of strings is discussed. We …
various contexts. In this chapter its adaptation to the domain of strings is discussed. We …
Complexities of the centre and median string problems
F Nicolas, E Rivals - Annual Symposium on Combinatorial Pattern …, 2003 - Springer
Given a finite set of strings, the median string problem consists in finding a string that
minimizes the sum of the distances to the strings in the set. Approximations of the median …
minimizes the sum of the distances to the strings in the set. Approximations of the median …
A new iterative algorithm for computing a quality approximate median of strings based on edit operations
J Abreu, JR Rico-Juan - Pattern Recognition Letters, 2014 - Elsevier
This paper presents a new algorithm that can be used to compute an approximation to the
median of a set of strings. The approximate median is obtained through the successive …
median of a set of strings. The approximate median is obtained through the successive …
Median strings for k-nearest neighbour classification
CD Martınez-Hinarejos, A Juan… - Pattern Recognition Letters, 2003 - Elsevier
Modelling a (large) set of garbled patterns with a prototype is an important issue in pattern
recognition. When strings are used as object representations, the representative prototype …
recognition. When strings are used as object representations, the representative prototype …
Reducing the computational cost of computing approximated median strings
Abstract The k-Nearest Neighbour (k-NN) rule is one of the most popular techniques in
Pattern Recognition. This technique requires good prototypes in order to achieve good …
Pattern Recognition. This technique requires good prototypes in order to achieve good …
Consensus learning for sequence data
A Nienkötter, X Jiang - Data Mining in Time Series and Streaming …, 2018 - World Scientific
Learning a prototype from a set of given objects is a core problem in machine learning, data
mining, and pattern recognition. A commonly used approach to consensus learning is to …
mining, and pattern recognition. A commonly used approach to consensus learning is to …
A new self-organizing map for dissimilarity data
T Ho-Phuoc, A Guerin-Dugue - Encyclopedia of Artificial Intelligence, 2009 - igi-global.com
Abstract The Self-Organizing Map (Kohonen, 1997) is an effective and a very popular tool for
data clustering and visualization. With this method, the input samples are projected into a …
data clustering and visualization. With this method, the input samples are projected into a …
A new adaptation of Self-Organizing Map for dissimilarity data
T Ho-Phuoc, A Guérin-Dugué - … on Artificial Neural Networks, IWANN 2007 …, 2007 - Springer
Abstract Adaptation of the Self-Organizing Map to dissimilarity data is of a growing interest.
For many applications, vector representation is not available and but only proximity data …
For many applications, vector representation is not available and but only proximity data …