In this paper we briefly study the basic idea of Akaike's (1973) information criterion (AIC).
Then, we present some recent developments on a new entropic or information complexity …

Radar emitter classification is a special application of data clustering for classifying unknown
radar emitters from received radar pulse samples. The main challenges of this task are the …

This paper presents 'hidden Markov experts', a framework for predicting conditional
probability distributions of future values of a time series. On daily S&P500 data, the out‐of …

CONTENTS 2.1 Introduction............................................................. 15 2.2 What is Information
Complexity: ICOMP?................................ 17 2.3 Information Criteria for Multiple Regression …

One of the second generation of computer scientists, Chris Wallace completed his tertiary
education in 1959 with a Ph. D. in nuclear physics, on cosmic ray showers, under Dr Paul …

The Bayesian Information Criterion (BIC) is a widely adopted method for audio
segmentation, and has inspired a number of dominant algorithms for this application. At …

This paper proposes an unsupervised algorithm for learning a finite Dirichlet mixture model.
An important part of the unsupervised learning problem is determining the number of …

Model identification is a necessary component of modern science. Model misspecification is
a major, if not the dominant, source of error in the quantification of most scientific evidence …

Robust acoustic segmentation has become a critical issue in order to apply speech
recognition to audio streams with variable acoustic content, eg radio programs. Many …

This paper proposes an unsupervised learning algorithm for a finite mixture model of shifted-
scaled Dirichlet distributions. Maximum likelihood and Newton raphson approaches are …