Our goal is to achieve a musical ensemble among a robot and human musicians where the robot listens to the music with its own microphones. The main issues are (1) robust beat-tracking since the robot hears its own generated sounds in addition to the accompanied music, and (2) robust synchronizing its performance with the accompanied music even if humans’ musical performance fluctuates. This pap...

Multiple-pulse NMR experiments are a powerful tool for the investigation of molecules with coupled nuclear spins. The product operator formalism provides a way to understand the quantum evolution of an ensemble of weakly coupled spins in such experiments using some of the more intuitive concepts of classical physics and semi-classical vector representations. In this paper I present a new way in...

Rainfall forecasting is an important research topic in disaster prevention and reduction. The characteristic of rainfall involves a rather complex systematic dynamics under the influence of different meteorological factors, including linear and nonlinear pattern. Recently, many approaches to improve forecasting accuracy have been introduced. Artificial neural network (ANN), which performs a non...

In this paper, we propose a method of estimating individual micro data from aggregated open data based on semisupervised learning and conditional probability. Firstly, the proposed method collects aggregated open data and support data, which are related to the individual micro data to be estimated. Then, we perform the locality sensitive hashing (LSH) algorithm to find a subset of the support d...

Ensemble learning combines several individual models to obtain better generalization performance. Currently, deep architectures are showing performance compared the shallow or traditional models. Deep ensemble combine advantages of both as well such that final model has This paper reviews state-of-art and hence serves an extensive summary for researchers. The broadly categorized into bagging, b...

The eigenvalue density for members of the Gaussian orthogonal and unitary ensembles follows the Wigner semi-circle law. If the Gaussian entries are all shifted by a constant amount c/(2N)1/2, where N is the size of the matrix, in the large N limit a single eigenvalue will separate from the support of the Wigner semi-circle provided c > 1. In this study, using an asymptotic analysis of the secul...

In semi supervised clustering is one of the major tasks and aims at grouping the data objects into meaningful classes (clusters) such that the similarity of objects within clusters is maximized and the similarity of objects between clusters is minimized. The dataset sometimes may be in mixed nature that is it may consist of both numeric and categorical type of data. Naturally these two types of...

This paper investigates the problem of image classification with limited or no annotations, but abundant unlabeled data. The setting exists in many tasks such as semi-supervised image classification, image clustering, and image retrieval. Unlike previous methods, which develop or learn sophisticated regularizers for classifiers, our method learns a new image representation by exploiting the dis...

Local tag structures have become frequent through Web 2.0: Users "tag" their data without specifying the underlying semantics. Every user annotates items in an individual way using the own labels. Even if two users happen to use a tag with the same name, it need not mean the same. Moreover, within the collection of a single user, media items are tagged multiply using different aspects, e.g., to...