In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Abstract. A method is proposed to determine the similarity of a collection of time series. As a first step, one extracts events from the time series, in other words, one converts e...
In this paper, we try to develop a machine learning-based virus email detection method. The key feature of this paper is employing Mail Header and Encoding Anomaly(MHEA) [1]. MHEA ...
We present a category learning vector quantization (cLVQ) approach for incremental and life-long learning of multiple visual categories where we focus on approaching the stability-...
Stephan Kirstein, Heiko Wersing, Horst-Michael Gro...
Abstract. The amygdala is the neural structure that acts as an evaluator of potentially threatening stimuli. We present a biologically plausible model of the visual fear conditioni...
Abstract. We study synchronization phenomena in a pair of integrateand-fire (IF) oscillators with the width of an action potential. They have slightly different periodic firings ea...
A number of learning machines used in information science are not regular, but rather singular, because they are non-identifiable and their Fisher information matrices are singula...
This paper presents a novel and notable swarm approach to evolve an optimal set of weights and architecture of a neural network for classification in data mining. In a distributed ...
Bump modeling is a method used to extract oscillatory bursts in electrophysiological signals, who are most likely to be representative of local synchronies. In this paper we presen...