The second edition of this extensively revised and updated text is a result of the positive
feedback and constructive suggestions received from academics and students alike. It …

In this paper, we explore the problem of deep multi-view subspace clustering framework
from an information-theoretic point of view. We extend the traditional information bottleneck …

Weighted multi-view clustering (MVC) aims to combine the complementary information of
multi-view data (such as image data with different types of features) in a weighted manner to …

This article studies the multimodal named entity recognition (MNER) and multimodal relation
extraction (MRE), which are important for content analysis and various applications. The …

In recent years, the acquisition of image and video information for processing, analysis,
understanding, and exploitation of the underlying content in various applications, ranging …

The Information Bottleneck method is a powerful and generic tool from the field of machine
learning. It compresses an observation to a quantized variable while attempting to preserve …

We introduce the matrix-based Rényi's α-order entropy functional to parameterize Tishby et
al. information bottleneck (IB) principle [1] with a neural network. We term our methodology …

This paper deals with the implementation of Simple Algorithm for detection of range and
shape of tumour in brain MR images. Tumour is an uncontrolled growth of tissues in any part …

Segmentation is an important aspect of medical image processing, where Clustering
approach is widely used in biomedical applications particularly for brain tumor detection in …

This survey is for the remembrance of one of the creators of the information bottleneck
theory, Prof. Naftali Tishby, passing away at the age of 68 on August, 2021. Information …