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pro vyhledávání: '"Luke K. McDowell"'
Autor:
David W. Aha, Luke K. McDowell
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 11:1-37
Many analysis tasks involve linked nodes, such as people connected by friendship links. Research on link-based classification (LBC) has studied how to leverage these connections to improve classification accuracy. Most such prior research has assumed
Autor:
David Liedtka, Luke K. McDowell
Publikováno v:
DSAA
Prior work has demonstrated that multiple methods for link-based classification (LBC) can substantially improve accuracy when the nodes of interest are interconnected. To date, however, very little work has considered how methods for LBC could be app
Autor:
Ryan N. Rakvic, Owens Walker, Dane Brown, Luke K. McDowell, James Shey, Jacob Melton, Justin A. Blanco, Hau Ngo, Kevin D. Fairbanks
Publikováno v:
2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER).
With the increasing demand for faster reliable secondary storage, Solid State Drives (SSDs) have provided a viable replacement for Hard Disk Drives (HDDs). SSDs contain NAND flash memory components and a processor that executes firmware at the device
Autor:
Joshua R. King, Luke K. McDowell
Publikováno v:
DSAA
Many classification problems involve nodes that have a natural connection between them, such as links between people, pages, or social network accounts. Recent work has demonstrated how to learn relational dependencies from these links, then leverage
Publikováno v:
Journal of Artificial Intelligence Research. 45:363-441
Relational data representations have become an increasingly important topic due to the recent proliferation of network datasets (e.g., social, biological, information networks) and a corresponding increase in the application of Statistical Relational
Autor:
Luke K. McDowell
Publikováno v:
DSAA
Many information tasks involve objects that are explicitly or implicitly connected in a network (or graph), such as webpages connected by hyperlinks or people linked by “friendships” in a social network. Research on link-based classification (LBC
Publikováno v:
Formalisms for Reuse and Systems Integration ISBN: 9783319165769
Data describing networks such as social networks, citation graphs, hypertext systems, and communication networks is becoming increasingly common and important for analysis. Research on link-based classification studies methods to leverage connections
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0f125c2bbe7181833222f5f5cba3e1f
https://doi.org/10.1007/978-3-319-16577-6_10
https://doi.org/10.1007/978-3-319-16577-6_10
Publikováno v:
ACM Transactions on Computer Systems. 21:314-340
Modern superscalar processors rely heavily on speculative execution for performance. For example, our measurements show that on a 6-issue superscalar, 93% of committed instructions for SPECINT95 are speculative. Without speculation, processor resourc
Publikováno v:
IRI
Many information tasks involve objects that are explicitly or implicitly connected in a network, such as webpages connected by hyperlinks or people linked by "friendships" in a social network. Research on link-based classification (LBC) has studied h
Autor:
David W. Aha, Luke K. McDowell
Publikováno v:
CIKM
Many classification tasks involve linked nodes, such as people connected by friendship links. For such networks, accuracy might be increased by including, for each node, the (a) labels or (b) attributes of neighboring nodes as model features. Recent