In this paper we present a methodology and techniques for generating cycle-accurate macro-models for RTlevel power analysis. The proposed macro-model predicts not only...
Despite the growing interest for component-based systems, few works tackle the question of the trust we can bring into a component. This paper presents a method and a tool for bui...
Abstract--We present an algorithm that coevolves fitness predictors, optimized for the solution population, which reduce fitness evaluation cost and frequency, while maintaining ev...
This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for USD/JPY exchange rates forecasting. Previous work often used time series techniques and neural networks (NN...
Meysam Alizadeh, Roy Rada, Akram Khaleghei Ghoshe ...
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...