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» Information Flows in Causal Networks
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IJCAI
2001
13 years 6 months ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
NDSS
2005
IEEE
13 years 11 months ago
Enriching Intrusion Alerts Through Multi-Host Causality
Current intrusion detection systems point out suspicious states or events but do not show how the suspicious state or events relate to other states or events in the system. We sho...
Samuel T. King, Zhuoqing Morley Mao, Dominic G. Lu...
ECIS
2000
13 years 6 months ago
Towards a Grounded Theory of Information Systems for the International Firm: Critical Variables and Causal Networks
-International Information Systems, often of critical importance for the operations of the multinational enterprise, are poorly researches and there is a dearth of theoretical fram...
Hans P. Lehmann
UAI
1993
13 years 6 months ago
Using Causal Information and Local Measures to Learn Bayesian Networks
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Wai Lam, Fahiem Bacchus
ESOP
2000
Springer
13 years 9 months ago
Secure Information Flow as Typed Process Behaviour
Abstract. We propose a new type discipline for the -calculus in which secure information flow is guaranteed by static type checking. Secrecy levels are assigned to channels and are...
Kohei Honda, Vasco Thudichum Vasconcelos, Nobuko Y...