Pelleg, D., & Moore, A. (2002). Using tarjan's red rule for fast dependency tree construction. NIPS 15.  Home/Search Document Details and Download
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Tractable Learning of Large Bayes Net Structures from Sparse.. - Anna Goldenberg Anya Self-citation (Moore) (Correct)
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Pelleg, D., & Moore, A. (2002). Using tarjan's red rule for fast dependency tree construction. NIPS 15.
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Pelleg, D. and Moore, A. (2002). Using Tarjan's Red Rule for Fast Dependency Tree Construction. In Proceedings of Neural Information Processing Systems, volume 14.
Using Tarjan's Red Rule for Fast Dependency Tree Construction - Pelleg, Moore (2002) (1 citation) Self-citation (Pelleg Moore) (Correct)
....of Z. We thus can derive a two sided confidence interval for Z i = x i y i with probability 1 for some user specified , typically 1 . Given this interval, computing an interval for is straightforward. Categorical data can be treated similarly; for lack of space we refer the reader to [13] for the details. 4 The full algorithm As we argued, the MIST algorithm is capable of using partial information about edge weights. We have also shown how to derive confidence intervals on edge weights. We now combine the two and give an efficient dependency tree algorithm. We largely follow ....
Dan Pelleg and Andrew Moore. Using Tarjan's red rule for fast dependency tree construction. Technical Report CMU-CS-02-116, Carnegie-Mellon University, 2002.
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D. Pelleg, A. Moore, Using Tarjan's red rule for fast dependency tree construction, in: S. Becker, S. Thrun, K. Obermayer (Eds.), Advances in Neural Information Processing Systems 15, MIT Press, Cambridge, MA, 2003, pp. 825-- 832.
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