We solve a weakly supervised regression problem. Under “weakly” we understand that for
some training points the labels are known, for some unknown, and for others uncertain due …

This paper proposes a semi-supervised classification method which combines machine
learning regularization framework and cluster ensemble approach. We use the low-rank …

In this paper, we solve a semi-supervised regression problem. Due to the lack of knowledge
about the data structure and the presence of random noise, the considered data model is …

Background Advances in molecular biology have resulted in big and complicated data sets,
therefore a clustering approach that able to capture the actual structure and the hidden …

In this paper, we consider semi-supervised regression problem. The proposed method can
be divided into two steps. In the first step, a number of variants of clustering partition are …

We solve a weakly supervised regression problem. Under" weakly" we understand that for
some training points the labels are known, for some unknown, and for others uncertain due …

This paper presents a method for some semi-supervised and supervised classification
problems based on properties of the averaged co-association matrix obtained with a cluster …

In this paper, we study the properties of the KCCE algorithm (Kernel-based Classification
with Cluster Ensemble) proposed in our previous publication. Different strategies for …

Recently, researchers proposed heuristic frameworks which are based on the Wisdom of
Crowds in order to evaluate and select the basic results. In these methods, basic results are …

In this paper, we solve a semi-supervised regression problem. Due to the luck of knowledge
about the data structure and the presence of random noise, the considered data model is …