Appropriate maintenance of industrial equipment keeps production systems in good health
and ensures the stability of production processes. In specific production sectors, such as the …

Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …

A general framework for constructing and using probabilistic models of complex systems that
would enable a computer to use available information for making decisions. Most tasks …

We review machine learning methods employing positive definite kernels. These methods
formulate learning and estimation problems in a reproducing kernel Hilbert space (RKHS) of …

We present a family of margin based online learning algorithms for various prediction tasks.
In particular we derive and analyze algorithms for binary and multiclass categorization …

Sequence classification has a broad range of applications such as genomic analysis,
information retrieval, health informatics, finance, and abnormal detection. Different from the …

Many tasks involve predicting a large number of variables that depend on each other as well
as on other observed variables. Structured prediction methods are essentially a combination …

Learning general functional dependencies between arbitrary input and output spaces is one
of the key challenges in computational intelligence. While recent progress in machine …

Learning general functional dependencies is one of the main goals in machine learning.
Recent progress in kernel-based methods has focused on designing flexible and powerful …

We develop a theoretical analysis of the performance of the regularized least-square
algorithm on a reproducing kernel Hilbert space in the supervised learning setting. The …