The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI, functional Magnetic Resonance Imaging) to ...
Michael A. Arbib, Aude Billard, Marco Iacoboni, Er...
Abstract. We present a Context Ultra-Sensitive Approach based on two-step Recommender systems (CUSA-2step-Rec). Our approach relies on a committee of profile-specific neural networ...
Polarity shifting marked by various linguistic structures has been a challenge to automatic sentiment classification. In this paper, we propose a machine learning approach to inco...
Shoushan Li, Sophia Yat Mei Lee, Ying Chen, Chu-Re...
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
This paper describes an empirical study to investigate the performance of a wide range of classifiers deployed in applications to classify biometric data. The study specifically re...