One of the most critical tasks for improving data quality and increasing the reliability of data
analytics is Entity Resolution (ER), which aims to identify different descriptions that refer to …

Many real-world relations can be represented by signed networks with positive and negative
links, as a result of which signed network analysis has attracted increasing attention from …

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 …

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 …

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 …

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 …

Preprocessing, or data reduction, is a standard technique for simplifying and speeding up
computation. Written by a team of experts in the field, this book introduces a rapidly …

We describe a system that automatically generates from a curated database a collection of
short conventional publications—citation summaries—that describe the contents of various …