The growing information infrastructure in a variety of disciplines involves an increasing
requirement for efficient data mining techniques. Fast dimensionality reduction methods are …

List of References on Evolutionary Multiobjective Optimization Page 1 List of References on
Evolutionary Multiobjective Optimization Carlos A. Coello Coello ccoello@cs.cinvestav.mx …

In this paper we present an evolutionary algorithm to tackle the subspace clustering
problem. Subspace clustering is recognized as more difficult than standard clustering since …

Recent technical advances have facilitated the massive acquisition of data described by a
large number of measurable properties (high dimensional datasets). New technologies have …

Subspace clustering identifies the attribute support for each cluster as well as identifying the
location and number of clusters. In the most general case, attributes associated with each …

We present an algorithm for generating subspace clusterings of large data sets with many
attributes. An evolutionary algorithm is used to form groups of relevant attributes. Those …

New emerging high-dimensional data sets have made traditional clustering algorithms
increasingly inefficient. More sophisticated approaches are required to cope with the …

Manifold clustering, also known as submanifold learning, is the task to embed patterns in
submanifolds with different characteristics. This paper proposes a hybrid approach of …

Massive volumes of high-dimensional data that evolve over time are continuously collected
by contemporary information processing systems, which bring up the problem of organizing …

Unsupervised regression is a dimensionality reduction method that allows embedding high-
dimensional patterns in low-dimensional latent spaces. In the line of research on iterative …