This review covers recent results concerning the estimation of large covariance matrices
using tools from Random Matrix Theory (RMT). We introduce several RMT methods and …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

What matters in people's social lives? What motivates and inspires our society? How do we
enact what we know? Since the first edition published in 1980, Content Analysis has helped …

Abstract The Probabilistic Relevance Framework (PRF) is a formal framework for document
retrieval, grounded in work done in the 1970–1980s, which led to the development of one of …

The advent of machine learning (ML) and Artificial intelligence (AI) has brought about a
significant transformation across multiple industries, as it has facilitated the automation of …

This paper studies unsupervised/self-supervised whole-graph representation learning,
which is critical in many tasks such as molecule properties prediction in drug and material …

Currently, most approaches to retrieving textual materials from scientific databases depend
on a lexical match between words in users' requests and those in or assigned to documents …

In this paper, we describe the influence of physical proximity on the development of
collaborative relationships between scientific researchers and on the execution of their work …

We propose a principled approach to summarization of visual data (images or video) based
on optimization of a well-defined similarity measure. The problem we consider is re-targeting …

Graph-level representations are critical in various real-world applications, such as predicting
the properties of molecules. However, in practice, precise graph annotations are generally …