Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Scott Freitas"'
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4eb708bb820a3054d60294408b9fe59
https://doi.org/10.1109/bigdata52589.2021.9671807
https://doi.org/10.1109/bigdata52589.2021.9671807
Publikováno v:
IEEE BigData
Deep learning models are being integrated into a wide range of high-impact, security-critical systems, from self-driving cars to medical diagnosis. However, recent research has demonstrated that many of these deep learning architectures are vulnerabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2de78aae898f83a48751294de415f3de
https://doi.org/10.1109/bigdata50022.2020.9378303
https://doi.org/10.1109/bigdata50022.2020.9378303
Autor:
Siwei Li, Duen Horng Chau, Omar Shaikh, Haekyu Park, Zijie J. Wang, Anish Upadhayay, Susanta Routray, Zhiyan Zhou, Matthew Hull, Scott Freitas
Publikováno v:
CIKM
Graph data have become increasingly common. Visualizing them helps people better understand relations among entities. Unfortunately, existing graph visualization tools are primarily designed for single-person desktop use, offering limited support for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91a24d16038e849d14040e9784d3b930
http://arxiv.org/abs/2008.11844
http://arxiv.org/abs/2008.11844
Publikováno v:
CIKM
Network robustness plays a crucial role in our understanding of complex interconnected systems such as transportation, communication, and computer networks. While significant research has been conducted in the area of network robustness, no comprehen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae377d970539128343efcb80988036b9
http://arxiv.org/abs/2006.05648
http://arxiv.org/abs/2006.05648
Publikováno v:
WWW
In recent years, significant attention has been devoted towards integrating deep learning technologies in the healthcare domain. However, to safely and practically deploy deep learning models for home health monitoring, two significant challenges mus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::622603025d2a3bb46b78e7d078048b70
http://arxiv.org/abs/2001.11363
http://arxiv.org/abs/2001.11363
Publikováno v:
IEEE BigData
Local graph partitioning is a key graph mining tool that allows researchers to identify small groups of interrelated nodes (e.g., people) and their connective edges (e.g., interactions). As local graph partitioning focuses primarily on the graph stru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::789a0b85842f05863e03451205b12c02
https://doi.org/10.1109/bigdata.2018.8622227
https://doi.org/10.1109/bigdata.2018.8622227
Publikováno v:
CIKM
In this paper we present a web-based prototype for an explainable ranking algorithm in multi-layered networks, incorporating both network topology and knowledge information. While traditional ranking algorithms such as PageRank and HITS are important
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1040bb33713afddaf04ba8829d84be55
https://doi.org/10.1145/3269206.3269224
https://doi.org/10.1145/3269206.3269224
Publikováno v:
CIKM
This research focuses on accelerating the computational time of two base network algorithms (k-simple shortest paths and minimum spanning tree for a subset of nodes)---cornerstones behind a variety of network connectivity mining tasks---with the goal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55d4914651bc75cb40e171df7012056d
https://doi.org/10.1145/3132847.3133170
https://doi.org/10.1145/3132847.3133170