We prove a result, similar to the ones known as Ishihara's First and Second Trick, for sequences of functions.

Generative models dealing with modeling a joint data distribution are generally autoencoder, or GAN based. Both have pros and cons, generating blurry images being unstable in training. We propose new generative model resembling classical transforming Gaussian noise into space without adversarial optimization. Training of the proposed is two-step procedure. First, we train an autoencoder-based a...

A data-driven soft-sensor modelling approach based on dynamic kernel slow feature analysis (KSFA) is proposed in this paper. Slow a extraction method that aims to extract slowly varying features can capture the driving forces behind data. However, there are situations where linear SFA (LSFA) cannot due nonlinear relationships between and input signals. KSFA extension of LSFA utilises trick map ...

We propose a family of kernels for structured objectswhich is based on the bag-of-components paradigm. Rather than decomposing each complex object into the single histogram of its components, we use for each object a family of nested histograms, where each histogram in this hierarchy describes the object seen from an increasingly granular perspective. We use this hierarchy of histograms to defi...

In the domain of industrial process modeling and control, Hammerstein model has been used widely to describe a class of nonlinear systems. Goethals et al. (2005) proposed a method based on Least Squares Support Vector Machines (LSSVM) to identify the input-output relationship of the Hammerstein model. Unfortunately, as the data points grow, this kernel learning approach costs much time correspo...

In leaf image classification or retrieval fields, hybrid features are widely used to represent the information in various aspects by combining a number of sub-features linearly. However, the importance degrees of sub-features are often ignored by assigning the weights in an ad-hoc fashion without a solid theoretical basis. In this paper, a new type of adaptive hybrid features is proposed by usi...

The Kruskal Count is a card trick invented by Martin Kruskal in which a magician “guesses” a card selected by a subject according to a certain counting procedure. With high probability the magician can correctly “guess” the card. The success of the trick is based on a mathematical principle related to coupling models for Markov chains. This paper analyzes in detail two simplified variants of th...