We discuss a variety of clustering problems arising in combinatorial applications and in classifying objects into homogenous groups. For each problem we discuss solution strategies that work well in practice. We also discuss the importance of careful modelling in clustering problems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44350/1/10614_2004_Article_BF00121636.pd
Clustering is often formulated as a discrete optimization problem. The objective is to find, among a...
I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russia...
Clustering is often formulated as a discrete optimization problem. The objective is to find, among a...
We discuss a variety of clustering problems arising in combinatorial applications and in classifying...
Abstract. We discuss a variety of clustering problems arising in combinatorial pplications and in cl...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
The problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization. An ...
The study of human performance on discrete optimization problems has a considerable history that spa...
Partition-based clustering is the task of partitioning a dataset in a number of groups of examples, ...
This paper analyses the data clustering problem from the continuous black-box optimization point of ...
Clustering objects into groups is usually done using a statistical heuristic or an optimisation. The...
We propose a novel clustering-based model-building evolutionary algorithm to tackle optimization pro...
Abstract. This paper analyses the data clustering problem from the continuous black-box optimization...
Clustering is often formulated as a discrete optimization problem. The objective is to find, among a...
I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russia...
Clustering is often formulated as a discrete optimization problem. The objective is to find, among a...
We discuss a variety of clustering problems arising in combinatorial applications and in classifying...
Abstract. We discuss a variety of clustering problems arising in combinatorial pplications and in cl...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
The problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization. An ...
The study of human performance on discrete optimization problems has a considerable history that spa...
Partition-based clustering is the task of partitioning a dataset in a number of groups of examples, ...
This paper analyses the data clustering problem from the continuous black-box optimization point of ...
Clustering objects into groups is usually done using a statistical heuristic or an optimisation. The...
We propose a novel clustering-based model-building evolutionary algorithm to tackle optimization pro...
Abstract. This paper analyses the data clustering problem from the continuous black-box optimization...
Clustering is often formulated as a discrete optimization problem. The objective is to find, among a...
I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russia...
Clustering is often formulated as a discrete optimization problem. The objective is to find, among a...