89 citations · 157 across the 10 of their papers we have counts for
10 papers
BARD: A structured technique for group elicitation of Bayesian networks to support analytic reasoning
Ann E. Nicholson, Kevin B. Korb, Erik P. Nyberg +13
In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is…
Latent Variable Discovery Using Dependency Patterns
Xuhui Zhang, Kevin B. Korb, Ann E. Nicholson +1
The causal discovery of Bayesian networks is an active and important research area, and it is based upon searching the space of causal models for those which can best explain a pat…
Structured Prediction of Sequences and Trees using Infinite Contexts
Ehsan Shareghi, Gholamreza Haffari, Trevor Cohn +1
Linguistic structures exhibit a rich array of global phenomena, however commonly used Markov models are unable to adequately describe these phenomena due to their strong locality a…
HetFHMM: A novel approach to infer tumor heterogeneity using factorial Hidden Markov model
Gholamreza Haffari, Zhaoxiang Cai, Mohammad S. Rahman +1
Cancer arises from successive rounds of mutations which generate tumor cells with different genomic variation i.e. clones. For drug responsiveness and therapeutics, it is necessary…
Proximity-Based Non-uniform Abstractions for Approximate Planning
Jiri Baum, Ann E. Nicholson, Trevor I. Dix
In a deterministic world, a planning agent can be certain of the consequences of its planned sequence of actions. Not so, however, in dynamic, stochastic domains where Markov decis…
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (2013)
Ann Nicholson, Padhriac Smyth
This is the Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, which was held in Bellevue, WA, August 11-15, 2013