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AMAI
2004
Springer
14 years 29 days ago
Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
Dmitri A. Dolgov, Edmund H. Durfee
JCB
2007
198views more  JCB 2007»
13 years 7 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
IDA
2003
Springer
14 years 23 days ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu
IJCAI
2003
13 years 9 months ago
Bayesian Information Extraction Network
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Leonid Peshkin, Avi Pfeffer
WWW
2008
ACM
14 years 8 months ago
Analyzing search engine advertising: firm behavior and cross-selling in electronic markets
The phenomenon of sponsored search advertising is gaining ground as the largest source of revenues for search engines. Firms across different industries have are beginning to adop...
Anindya Ghose, Sha Yang