Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Anthony J. Pinar"'
Autor:
Muhammad Aminul Islam, Timothy C. Havens, Derek T. Anderson, Anthony J. Pinar, Siva K. Kakula
Publikováno v:
IEEE Transactions on Fuzzy Systems. 29:2890-2901
Fuzzy integrals (FIs) are powerful aggregation operators that fuse information from multiple sources. The aggregation is parameterized using a fuzzy measure (FM), which encodes the worths of all subsets of sources. Since the FI is defined with respec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::726805ec76835c06dccffa58ed5fcea5
https://doi.org/10.1109/tfuzz.2020.3009722
https://doi.org/10.1109/tfuzz.2020.3009722
Autor:
Grant J. Scott, Muhammad Aminul Islam, Anthony J. Pinar, Bryce Murray, Derek T. Anderson, Timothy C. Havens, James M. Keller
Publikováno v:
IEEE Transactions on Emerging Topics in Computational Intelligence. 5:520-529
The modern era of machine learning is focused on data-driven solutions. While this has resulted in astonishing leaps in numerous applications, explainability has not witnessed the same growth. The reality is, most machine learning solutions are black
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55d9f9bc06926ad99fe8fb9ea24c5ebd
https://doi.org/10.1109/tetci.2020.3005682
https://doi.org/10.1109/tetci.2020.3005682
Publikováno v:
FUZZ-IEEE
The Choquet integral (ChI) is an aggregation operator defined with respect to a fuzzy measure (FM). The FM encodes the worth of all subsets of the sources of information that are being aggregated. The ChI is capable of representing many aggregation f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51e23adf40a265347403cdb508e39af5
https://doi.org/10.1109/fuzz45933.2021.9494505
https://doi.org/10.1109/fuzz45933.2021.9494505
Autor:
Stanton R. Price, Brendan Alvey, Timothy C. Havens, Adam Webb, Jessica L. Brown, Guilherme N. DeSouza, Anthony J. Pinar, Derek T. Anderson
Publikováno v:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III.
Cybersecurity of autonomous vehicles is a pertinent concern both for defense and also civilian systems. From self-driving cars to autonomous Navy vessels, malfunctions can have devastating consequences, including losses of life and infrastructure. Au
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65dc815bbfa5de1600f161a69193b74a
https://doi.org/10.1117/12.2587515
https://doi.org/10.1117/12.2587515
Publikováno v:
SSCI
The Choquet integral (ChI) is an aggregation operator defined with respect to a fuzzy measure (FM). The FM of a ChI encodes the worth of individual subsets of sources of information, and is an excellent tool for nonlinear aggregation. The monotonicit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::065b0f3e6036b444886fd62938550453
https://doi.org/10.1109/ssci47803.2020.9308471
https://doi.org/10.1109/ssci47803.2020.9308471
Publikováno v:
SMC
The Choquet Integral (ChI) is an aggregation operator defined with respect to a Fuzzy Measure (FM). The FM encodes the worth of all subsets of the sources of information that are being aggregated. The monotonicity and the boundary conditions of the F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef1378cb72474875f958bdfabe49a64e
https://doi.org/10.1109/smc42975.2020.9282999
https://doi.org/10.1109/smc42975.2020.9282999
Publikováno v:
FUZZ-IEEE
The ordered weighted average (OWA) operator is a well-known aggregation tool that is primarily used for decisionlevel fusion. However, the OWA is a convex sum, i.e., its learned coefficients are constrained to sum to one, and thus the output is restr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5df764020e58640c3a27bc655d978879
https://doi.org/10.1109/fuzz48607.2020.9177595
https://doi.org/10.1109/fuzz48607.2020.9177595
Publikováno v:
FUZZ-IEEE
The Choquet integral (ChI) is an aggregation function that is defined with respect to a fuzzy measure (FM). Many ChI-based decision aggregation methods have been proposed to learn the underlying FM. However, FM's boundary and monotonicity constraints
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc2e603a3c88e5b6fe64e6d7981540f2
https://doi.org/10.1109/fuzz48607.2020.9177657
https://doi.org/10.1109/fuzz48607.2020.9177657
Publikováno v:
IEEE Transactions on Fuzzy Systems. 26:1908-1922
The Choquet integral (ChI) is a parametric nonlinear aggregation function defined with respect to the fuzzy measure (FM). To date, application of the ChI has sadly been restricted to problems with relatively few numbers of inputs; primarily as the FM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac5b0813e1d3016c0abf39b1d7a27943
https://doi.org/10.1109/tfuzz.2017.2755002
https://doi.org/10.1109/tfuzz.2017.2755002
Publikováno v:
IEEE Transactions on Fuzzy Systems. 25:1403-1416
Kernel methods for classification is a well-studied area in which data are implicitly mapped from a lower-dimensional space to a higher dimensional space to improve classification accuracy. However, for most kernel methods, one must still choose a ke
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::241dd05c7d3239bc18a6b896ffc76721
https://doi.org/10.1109/tfuzz.2016.2633372
https://doi.org/10.1109/tfuzz.2016.2633372