“Weighting for more”: Enhancing characteristic-function based ICA with asymptotically optimal weighting

"Weighting for more": Enhancing characteristic-function based ICA with asymptotically optimal weighting

The CHaracteristic-function-Enabled Source Separation (CHESS) method for independent component analysis (ICA) is based on approximate joint diagonalization (AJD) of Hessians of the observations’ empirical log-characteristicfunction, taken at selected off-origin “processing points”. As previously observed in other contexts, the AJD performance can be significantly improved by optimal weighting, ...

Blind Source Separation based on Second-Order Statistics with Asymptotically Optimal Weighting

Optimal Weighting for Exam Composition

A problem faced by many instructors is that of designing exams that accurately assess the abilities of the students. Typically these exams are prepared several days in advance, and generic question scores are used based on rough approximation of the question difficulty and length. For example, for a recent class taught by the author, there were 30 multiple choice questions worth 3 points, 15 tr...

Novel Characteristic Function Based Criteria for Ica

We introduce two nonparametric independent component analysis (ICA) criteria based on factorization of characteristic functions. This approach has potential to separate wide class of distributions because characteristic function always exists. A simple criterion allowing for efficient search of the separating matrix and a more advanced criterion possessing desirable consistency property are pre...

Entropy Based Fuzzy Rule Weighting for Hierarchical Intrusion Detection

Predicting different behaviors in computer networks is the subject of many data mining researches. Providing a balanced Intrusion Detection System (IDS) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. Many of the proposed methods perform well in one of the two aspects, and concentrate on a su...