Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Leilani H. Gilpin"'
Autor:
Daphne Odekerken, Michał Araszkiewicz, Maria Dymitruk, Saurabh Chakravarty, Leilani H. Gilpin, Marie Garin, Ilaria Angela Amantea, Seyedeh Sajedeh Salehi, Robert van Doesburg
Publikováno v:
Artificial Intelligence and Law, 28(2), 267. Springer Netherlands
This is a report on the Doctoral Consortium co-located with the 17th International Conference on Artificial Intelligence and Law in Montreal.
Publikováno v:
DSAA
Complex machines, such as autonomous vehicles, are unable to reconcile conflicting behaviors between their underlying subsystems, which leads to accidents and other negative consequences. Existing approaches to error and anomaly detection are not equ
Autor:
Gregory Falco, Leilani H. Gilpin
Publikováno v:
2021 IEEE International Conference on Autonomous Systems (ICAS).
Autonomous cyber-physical systems are prone to error and failure. Verification and validation (V&V) is necessary for their safe, secure and resilient operations. Methods to detect faults in aerospace engineering (fault trees) and later adapted for se
Autor:
Leilani H. Gilpin, Antonio Chella, Murat Kocaoglu, Keiki Takadama, Prasad Tadepalli, Jamie Macbeth, Evan Patterson, Takashi Kido, Ioana Baldini, Andreas Martin, Ranjeev Mittu, Dylan Holmes, Knut Hinkelmann, David Gamez, William F. Lawless, Alessio Lomuscio, Clark Barrett, Carlos Cinelli, Donald A. Sofge, Shomir Wilson
Publikováno v:
AI Magazine. 40:59-66
Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic
Autor:
Leilani H. Gilpin
Publikováno v:
CISS
Ensuring autonomous systems can reason and anticipate unknown (erroneous) futures is important for safety, trust, and reliability. Self-driving is an important domain because of the difficulty in testing: not all erroneous scenarios cannot be covered
Publikováno v:
CHI Extended Abstracts
As conversational agents continue to replace humans in consumer contexts, voice interfaces must reflect the complexity of real-world human interaction to foster long-term customer relationships. Perceiving the personality traits of others based on th
Publikováno v:
HRI (Companion)
Understanding explanations of machine perception is an important step towards developing accountable, trustworthy machines. Furthermore, speech and vision are the primary modalities by which humans collect information about the world, but the linking
Publikováno v:
DSAA
There has recently been a surge of work in explanatory artificial intelligence (XAI). This research area tackles the important problem that complex machines and algorithms often cannot provide insights into their behavior and thought processes. XAI a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd68157dd13f4893d47d4d1faa886fcb
Autor:
Kumar Sricharan, Leilani H. Gilpin, Daniel Davies, Juan Liu, Aaron Wilson, John Alexis Guerra-Gomez, Eric A. Bier, Tomonori Honda
Publikováno v:
Scopus-Elsevier
AI Magazine; Vol 37, No 2: Summer 2016; 33-46
AI Magazine; Vol 37, No 2: Summer 2016; 33-46
Detection of fraud, waste, and abuse (FWA) is an important yet challenging problem. In this article, we describe a system to detect suspicious activities in large healthcare datasets. Each healthcare dataset is viewed as a heterogeneous network consi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::782f1f7421a05b018e52d14e06efb97b
http://www.scopus.com/inward/record.url?eid=2-s2.0-84961226438&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84961226438&partnerID=MN8TOARS