Proteins play important roles in living organisms, and their function is directly linked with
their structure. Due to the growing gap between the number of proteins being discovered …

Compared with radar and visible light imaging, infrared imaging has its own unique
advantages, and in recent years, it has become a topic of intense research interest. Robust …

Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared
search and track applications for self-defense or attacks. Consequently, an effective small …

The design of low-level image features is critical for computer vision algorithms. Orientation
histograms, such as those in SIFT~\cite {Lowe2004Distinctive} and HOG~\cite …

Kernel methods are among the most successful tools in machine learning and are used in
challenging data analysis problems in many disciplines. Here we provide examples where …

The present phase of Machine Learning is characterized by supervised learning algorithms
relying on large sets of labeled examples (n→∞). The next phase is likely to focus on …

When training deep networks it is common knowledge that an efficient and well generalizing
representation of the problem is formed. In this paper we aim to elucidate what makes the …

We provide a general mathematical framework for group and set equivariance in machine
learning. We define group equivariant non-expansive operators (GENEOs) as maps …

The present phase of Machine Learning is characterized by supervised learning algorithms
relying on large sets of labeled examples ($ n\to\infty $). The next phase is likely to focus on …

The aim of this letter is to propose a theory of deep restricted kernel machines offering new
foundations for deep learning with kernel machines. From the viewpoint of deep learning, it …