Classification

Short Sequence Classification Through Discriminable Linear Dynamical System

Linear dynamical system (LDS) offers a convenient way to reveal the unobservable structure behind the data. This makes it useful for data representation and explanatory analysis. An immediate limitation with this model is that most training …

Disturbance Grassmann Kernels for Subspace-Based Learning

In this paper, we focus on subspace-based learning problems, where data elements are linear subspaces instead of vectors. To handle this kind of data, Grassmann kernels were proposed to measure the space structure and used with classifiers, e.g., …

Sequential Data Classification in the Space of Liquid State Machines

This paper proposes a novel classification approach to carrying out sequential data classification. In this approach, each sequence in a data stream is approximated and represented by one state space model – liquid state machine. Each sequence is …