We propose a mathematical framework for query selection as a mechanism for reducing the cost of constructing information retrieval test collections. In particular, our mathematica...
Mehdi Hosseini, Ingemar J. Cox, Natasa Milic-Frayl...
In this paper, we propose a new wideband model order reduction method for interconnect circuits by using a novel adaptive sampling and error estimation scheme. We try to address t...
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
Li Shen, Yuan Qi, Sungeun Kim, Kwangsik Nho, Jing ...
In discretization of a continuous variable its numerical value range is divided into a few intervals that are used in classification. For example, Na¨ıve Bayes can benefit from...