The modern science of networks has brought significant advances to our understanding of
complex systems. One of the most relevant features of graphs representing real systems is …

In this survey we overview the definitions and methods for graph clustering, that is, finding
sets of “related” vertices in graphs. We review the many definitions for what is a cluster in a …

To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a
new pair of precision-recall measures of performance that treats errors of all types uniformly …

The goal of this paper is to advance the state-of-the-art of articulated pose estimation in
scenes with multiple people. To that end we contribute on three fronts. We propose (1) …

This paper considers the task of articulated human pose estimation of multiple people in real
world images. We propose an approach that jointly solves the tasks of detection and pose …

This book addresses some theoretical aspects of semisupervised learning (SSL). The book
is organized as a collection of different contributions of authors who are experts on this topic …

In this paper, we propose a novel edge-labeling graph neural network (EGNN), which
adapts a deep neural network on the edge-labeling graph, for few-shot learning. The …

Abstract Multi-Target Multi-Camera Tracking (MTMCT) tracks many people through video
taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images …

Often, in the real world, entities have two or more representations in databases. Duplicate
records do not share a common key and/or they contain errors that make duplicate matching …

Lexical Semantic Change detection, ie, the task of identifying words that change meaning
over time, is a very active research area, with applications in NLP, lexicography, and …