After Minsky and Papert (Perceptrons, MIT Press, Cambridge, 1969) showed the inability of perceptrons in solving nonlinearly separable problems, for several decades people misinterpreted it as an inherent weakness that is ...

Convolutional neural networks -CNNs- have become an essential tool for solving many machine vision and machine learning problems. A major element of these networks is the convolution operator which essentially computes the ...

In this paper we propose a new method for extending 1-D step edge detection filters to two dimensions via complex-valued filtering. Complex-valued filtering allows us to obtain edge magnitude and direction simultaneously. ...

Runtime reconfiguration is a fundamental requirement of many telecommunication applications which also has been addressed by management standards like CMIP, 3GPP TS 32.602, and NETCONF. Two basic commands considered by ...

مدل¬های گرافی احتمالاتی با لایه مخفی چارچوبی قدرتمند برای دسته¬بندی دنباله¬ای از داده¬ها ارائه می‌کنند. میدان تصادفی شرطی با حالات پنهان(HCRF) از جمله مدل¬های تفکیک‌کننده است که از لایه مخفی استفاده کرده و وزن¬های مشترکی ...

Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we consider the problem of optimizing a kernel ...

The goal of many tasks in the realm of sequence processing is to map a sequence of input data to a sequence of output labels. Long short-term memory (LSTM), a type of recurrent neural network (RNN), equipped with connectionist ...

Convolutional Kernel Networks -CKNs- are efficient multilayer kernel machines, which are constructed by approximating a convolution kernel with a mapping based on Gaussian functions. In this paper, we introduce a new ...

In this paper, a new method for PPI (proteinprotein interaction) prediction is proposed. In PPI prediction,

a reliable and sufficient number of training samples is not available, but a large number of unlabeled ...