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153
Dynamic Bayesian Networks: Representation, Inference and Learning
, 2002
"... Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and biosequence analysis, and KFMs have bee ..."
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Cited by 770 (3 self)
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) space instead of O(T); a simple way of using the junction tree algorithm for online inference in DBNs; new complexity bounds on exact online inference in DBNs; a new deterministic approximate inference algorithm called factored frontier; an analysis of the relationship between the BK algorithm and loopy
On the Pricing of Credit Spread Options: A TwoFactor HWBK Algorithm.’’ Working paper
 Artesia BC and University of California at Berkeley
, 2001
"... In this article we describe what a credit spread option (CSO) is and show a tree algorithm to price it. The tree algorithm we have opted for is a two factor model composed by a Hull and White (HW) one factor for the interest rate process and a BlackKarazinsky (BK) one factor for the default intensi ..."
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Cited by 3 (0 self)
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In this article we describe what a credit spread option (CSO) is and show a tree algorithm to price it. The tree algorithm we have opted for is a two factor model composed by a Hull and White (HW) one factor for the interest rate process and a BlackKarazinsky (BK) one factor for the default
The Factored Frontier Algorithm for Approximate Inference in DBNs
 In UAI
"... The Factored Frontier (FF) algorithm is a simple approximate inference algorithm for Dynamic Bayesian Networks (DBNs). It is very similar to the fully factorized version of the BoyenKoller (BK) algorithm, but instead of doing an exact update at every step followed by marginalisation (projection), i ..."
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Cited by 64 (4 self)
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The Factored Frontier (FF) algorithm is a simple approximate inference algorithm for Dynamic Bayesian Networks (DBNs). It is very similar to the fully factorized version of the BoyenKoller (BK) algorithm, but instead of doing an exact update at every step followed by marginalisation (projection
Numerical methods for computing angles between linear subspaces
, 1971
"... Assume that two subspaces F and G of a unitary space are defined.. as the ranges(or nullspacd of given rectangular matrices A and B. Accurate numerical methods are developed for computing the principal angles ek(F,G) and orthogonal sets of principal vectors u k 6 F and vk c G, k = 1,2,..., q = d ..."
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Cited by 164 (4 self)
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= dim(G) 2 dim(F). An important application in statistics is computing the canonical correlations uk = cos 8 k between two sets of variates. A perturbation analysis shows that the condition number for ek essentially is max(K(A),K(B)), where K denotes the condition number of a matrix. The algorithms
The BK inequality for pivotal sampling
, 2012
"... It is shown that the BK inequality holds for the (treeordered) pivotal sampling algorithm a.k.a. the Srinivasan sampling process. This is done via a mapping, which commutes with the □operation, from increasing sets of samples to sets of match sequences and an application of Reimer’s inequality. ..."
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It is shown that the BK inequality holds for the (treeordered) pivotal sampling algorithm a.k.a. the Srinivasan sampling process. This is done via a mapping, which commutes with the □operation, from increasing sets of samples to sets of match sequences and an application of Reimer’s inequality.
Quantifier elimination for approximate BKfactorization
, 2007
"... Factorization of linear partial differential operators (LPDOs) is a very wellstudied problem and a lot of pure existence theorems are known. The only known constructive factorization algorithm BealsKartashova (BK) factorization is presented in [1]). Its comparison with Hensel descent which is ..."
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Factorization of linear partial differential operators (LPDOs) is a very wellstudied problem and a lot of pure existence theorems are known. The only known constructive factorization algorithm BealsKartashova (BK) factorization is presented in [1]). Its comparison with Hensel descent which is
Maximum flows by incremental breadthfirst search
 IN ESA, LNCS 6942
, 2011
"... Maximum flow and minimum st cut algorithms are used to solve several fundamental problems in computer vision. These problems have special structure, and standard techniques perform worse than the specialpurpose BoykovKolmogorov (BK) algorithm. We introduce the incremental breadthfirst search (I ..."
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Cited by 13 (2 self)
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Maximum flow and minimum st cut algorithms are used to solve several fundamental problems in computer vision. These problems have special structure, and standard techniques perform worse than the specialpurpose BoykovKolmogorov (BK) algorithm. We introduce the incremental breadthfirst search
Charholi Bk. via Lohgaon Pune
"... Information age demands omnipresence of data. Large data sets are created, maintained and outsourced to the third party experts for data mining. Knowledge and patterns are extracted by using advanced data mining algorithms that assist the decision makers to ensure quick, correct and effective decisi ..."
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Information age demands omnipresence of data. Large data sets are created, maintained and outsourced to the third party experts for data mining. Knowledge and patterns are extracted by using advanced data mining algorithms that assist the decision makers to ensure quick, correct and effective
Off Singhad Road,Vadgaon(Bk),
"... Today images, multimedia are immensely important in information retrieval system. In existing relevance feedback technique, there is semantic gap between high level concepts and low level features of images as well as videos, another drawback is according to user requirement we cannot retrieve relev ..."
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requirement. To provide efficient and effective retrieval of content based multimedia data and images from multimedia database like video data, images by using relevance feedback technique and mining algorithm.
Intrinsic Disorder in the BK Channel and Its Interactome
"... The largeconductance Ca2+activated K+ (BK) channel is broadly expressed in various mammalian cells and tissues such as neurons, skeletal and smooth muscles, exocrine cells, and sensory cells of the inner ear. Previous studies suggest that BK channels are promiscuous binders involved in a multitude ..."
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associated proteins (BKAPS) from cytoplasmic and membrane/cytoskeletal regions, plus BK b and csubunits. Disorder was evaluated using the MFDp algorithm, which is a consensusbased predictor that provides a strong and competitive predictive quality and PONDR, which can determine long intrinsically disordered
Results 1  10
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153