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We study the problem of learning Bayesian network structures from data. Koivisto and Sood (2004) and Koivisto (2006) presented algorithms that can compute the exact marginal posterior probability ofâ€¦ (More)

- Jin Tian, Ru He, Lavanya Ram
- UAI
- 2010

We study the problem of learning Bayesian network structures from data. We develop an algorithm for finding the k-best Bayesian network structures. We propose to compute the posterior probabilitiesâ€¦ (More)

- Samik Basu, Arka P. Ghosh, Ru He
- ICFEM
- 2009

We study the problem of applying statistical methods for approximate model checking of probabilistic systems against properties encoded as PCTL formulas. Such approximate methods have been proposedâ€¦ (More)

- Ru He, Paul Jennings, Samik Basu, Arka P. Ghosh, Huaiqing Wu
- ASE
- 2010

We study the problem of statistical model checking of probabilistic systems for <b>PCTL</b> unbounded until property <b>P</b>Join<sub>p</sub>(Ã†<sub>1</sub><b>U</b>Ã†<sub>2</sub>) (where Join |X| {<,â€¦ (More)

- Ru He, Mohammad Ghavami, Hamid Aghvami
- 2007 IEEE 18th International Symposium onâ€¦
- 2007

This paper proposes a positioning routing algorithm for UWB ad hoc networks. The algorithm is deployed in two main scenarios: Multi-Coordinate System (MCS) and Unique Coordinate System (UCS). Aâ€¦ (More)

- Ru He, Jin Tian, Huaiqing Wu
- ArXiv
- 2015

We study the Bayesian model averaging approach to learning Bayesian network structures (DAGs) from data. We develop new algorithms including the first algorithm that is able to efficiently sampleâ€¦ (More)

- Ru He, Jin Tian, Huaiqing Wu
- 2014

- Ru He, Jiong Wang, Jin Tian, Cheng-Tao Chu, Bradley Mauney, Igor Perisic
- JASIST
- 2013

We study the problem of learning Bayesian network structures from data. Koivisto and Sood (2004) and Koivisto (2006) presented algorithms that can compute the exact posterior probability of aâ€¦ (More)

- Ru He, Jin Tian, Huaiqing Wu
- Journal of Machine Learning Research
- 2016

We study the Bayesian model averaging approach to learning Bayesian network structures (DAGs) from data. We develop new algorithms including the first algorithm that is able to efficiently sampleâ€¦ (More)

We study the problem of applying statistical methods for approximate model checking of probabilistic systems against properties encoded as PCTL formulas. Such approximate methods have been proposedâ€¦ (More)