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» Observational learning in an uncertain world
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LISA
2007
13 years 9 months ago
NetADHICT: A Tool for Understanding Network Traffic
Computer and network administrators are often confused or uncertain about the behavior of their networks. Traditional analysis using IP ports, addresses, and protocols are insuffi...
Hajime Inoue, Dana Jansens, Abdulrahman Hijazi, An...
RSS
2007
198views Robotics» more  RSS 2007»
13 years 8 months ago
CRF-Matching: Conditional Random Fields for Feature-Based Scan Matching
— Matching laser range scans observed at different points in time is a crucial component of many robotics tasks, including mobile robot localization and mapping. While existing t...
Fabio T. Ramos, Dieter Fox, Hugh F. Durrant-Whyte
AI
2008
Springer
13 years 6 months ago
MEBN: A language for first-order Bayesian knowledge bases
Although classical first-order logic is the de facto standard logical foundation for artificial intelligence, the lack of a built-in, semantically grounded capability for reasonin...
Kathryn B. Laskey
NIPS
2007
13 years 8 months ago
Learning and using relational theories
Much of human knowledge is organized into sophisticated systems that are often called intuitive theories. We propose that intuitive theories are mentally represented in a logical ...
Charles Kemp, Noah Goodman, Joshua B. Tenenbaum

Publication
253views
13 years 5 months ago
Multisensory Oddity Detection as Bayesian Inference
A key goal for the perceptual system is to optimally combine information from all the senses that may be available in order to develop the most accurate and unified picture possi...
Timothy Hospedales and Sethu Vijayakumar