Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Structuring conditional relationships in influence diagrams
Operations Research
Knowledge representation and inference in similarity networks and Bayesian multinets
Artificial Intelligence
Machine Learning
Probabilistic partial evaluation: exploiting rule structure in probabilistic inference
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Exploiting causal independence in Bayesian network inference
Journal of Artificial Intelligence Research
Structured arc reversal and simulation of dynamic probabilistic networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Bucket elimination: a unifying framework for probabilistic inference
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Three-Tier Clustering: An Online Citation Clustering System
WAIM '01 Proceedings of the Second International Conference on Advances in Web-Age Information Management
Acquisition Methods for Contextual Weak Independence
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
A Method for Detecting Context-Specific Independence in Conditional Probability Tables
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
On the Role of Contextual Weak Independence in Probabilistic Inference
AI '02 Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Exploiting Additive Structure in Factored MDPs for Reinforcement Learning
Recent Advances in Reinforcement Learning
Likelihood computations using value abstraction
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Sufficiency, separability and temporal probabilistic models
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Causality, simpson's paradox, and context-specific independence
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Local structure and determinism in probabilistic databases
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Probabilistic reasoning with undefined properties in ontologically-based belief networks
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
| Hi-index | 0.00 |
Context-specific independence (CSI) refers to conditional independencies that are true only in specific contexts. It has been found useful in various inference algorithms for Bayesian networks. This paper studies the role of CSI in general. We provide a characterization of the computational leverages offered by CSI without referring to particular inference algorithms. We identify the issues that need to be addressed in order to exploit the leverages and show how those issues can be addressed. We also provide empirical evidence that demonstrates the usefulness of CSI.