From Natural Language to Bayesian Networks (and back again)
42 mins 5 secs,
175.81 MB,
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44100 Hz,
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Description: |
Bex, F
Wednesday 28th September 2016 - 10:15 to 11:00 |
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Created: | 2016-10-05 12:18 |
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Collection: | Probability and Statistics in Forensic Science |
Publisher: | Isaac Newton Institute |
Copyright: | Bex, F |
Language: | eng (English) |
Distribution: | World (downloadable) |
Explicit content: | No |
Aspect Ratio: | 16:9 |
Screencast: | No |
Bumper: | UCS Default |
Trailer: | UCS Default |
Abstract: | Decision makers and analysts often use informal, linguistic concepts when they talk about a case: they tell the story that explains the evidence, or argue against a particular interpretation of the evidence. On the other hand, mathematicians and logicians present formal frameworks to precisely capture and support reasoning about evidence.
In this talk, I will show how different Artificial Intelligence techniques can be used to close the gap between these two extremes - messy, informal natural language and specific, well-defined formalisms such as Bayesian Networks. |
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MPEG-4 Video | 640x360 | 1.94 Mbits/sec | 612.53 MB | View | Download | |
WebM * | 640x360 | 570.39 kbits/sec | 175.81 MB | View | Download | |
iPod Video | 480x270 | 522.0 kbits/sec | 160.90 MB | View | Download | |
MP3 | 44100 Hz | 249.77 kbits/sec | 77.05 MB | Listen | Download | |
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