This paper presents a new kernel method for appearance-based object recognition, highly robust to noise and occlusion. It consists of a fully connected Markov Random Field that in...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
This paper explores in detail the use of Error Correcting Output Coding (ECOC) for learning text classifiers. We show that the accuracy of a Naive Bayes Classifier over text class...
This paper proposes a new classification method based on association rule mining. This association rule-based classifier is experimented on a real dataset; a database of medical i...
Alexandru Coman, Maria-Luiza Antonie, Osmar R. Za&...
In this paper, for the first time, a theory for evaluating dynamic noise margins of SRAM cells is developed analytically. The results allow predicting the transient error suscepti...
Bin Zhang, Ari Arapostathis, Sani R. Nassif, Micha...