Summary of the tree-structured SOM algorithm
Tree-Structured Neural Decoding
... decoding algorithm, we consider spike trains traveling through the auditory nerve, a bundle of about 30,000 neurons in the inner ear which originates from the basilar membrane situated in the ...
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Algorithm for Enumerating all Frequent Paths from Structurally Compressed Tree-Structured Data
... large tree-structured data without loss of information, it leads to reduction in running time needed to extract structural ...features. Tree-structured data can be described by an edge-labeled ...
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An Algorithm for Efficiently Generating Summary Paragraphs Using Tree Adjoining Grammar
... For illustration, refer again to the specific- lexicalisation in figure 5. Notice that @ occurs as the anchor of more than one tree. 6 These trees, predication part:- participleclause:item name ...
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Kernel Methods for Tree Structured Data
... of SOM-SD and the standard tree ...standard tree kernels are ...the SOM-SD can not formally guarantee to preserve the topology of the items in the input ...
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Tree-structured Classification for Multivariate Binary Responses
... to tree-structured methods for multivariate ...the tree-structured regression paradigm to multiple response settings and in particular to longitudinal ...the tree size. Keefer (2001) ...
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Foreground Segmentation with Tree-Structured Sparse RPCA
... Our algorithm is capable of adapting to slow-moving foreground objects in these sequences, all the while being able to discard non-genuine false-alarm foreground pixels with the robust foreground segmentation via ...
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Head First Linearization with Tree Structured Representation
... generation algorithm follows the left-to-right se- quential ...linearization algorithm, in which we generate the sequence starting from the head and expanding to both ...
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DETECTION OF MASQUERADERS USING TREE STRUCTURED SVM
... In addition, the structure of the incremental classifiers is assumed to be fixed, and they cannot address the problem of so-called concept drift and shift [30]. By drift, they refer to a modification of the concept ...
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Optimization of a Fast Transform Structured as a Convolutional Tree
... sparsifying algorithm is always proportional to the numerical complexity of the matrix-vector ...minimization algorithm (PALMTREE) allowing Curvelet or Wavelet- packet transforms to be approximated with ...
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In-Memory Storage for Labeled Tree-Structured Data
... For each node, v, of W visited during the traversal, if the range of at least one of v’s children is contained entirely in [p, q], then we compute z v = LCA(x v , y v ) in B(v). We also perform a path summary ...
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IMPLEMENTATION OF ANONYMIZING COLLECTIONS OF TREE-STRUCTURED DATA
... but covers attackers who have only values as background knowledge, so it is not suitable for our data model. [45] pro-posed the application of disassociation in set-valued data, where a transaction could be split in two ...
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The Structured Weighted Violations Perceptron Algorithm
... assignment for each of the erroneous arcs where all other words are assigned their correct arc (according to the gold tree) except for that specific arc which is kept as in the bottom tree. Then, higher ...
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A parallel algorithm for the extraction of structured motifs
... each internal node has at least two children each edge is labeled with a nonempty substring of S no two edges out of a node can have edge-labels beginning with the same character The key feature of the suffix tree ...
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Reasoning About Integrity Constraints for Tree-Structured Data
... our algorithm reveals that it is double exponential only in the maximal number ` of variables in the constraints, which appears in two roles: in the exponent of the bound on the number of data values stored in ...
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Tree Structured Dirichlet Processes for Hierarchical Morphological Segmentation
... clustering algorithm (Can and Manandhar 2012). In that algorithm, a single tree is learned that corresponds to a hierarchical organization of morphological ...of tree structures. Within each ...
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Min-energy voltage allocation for tree-structured tasks
... include tree-structured job sets which can arise from executing recursive procedure calls, and job sets with limited time overlap among ...O(P) algorithm where P is the tree’s total path ...the ...
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Structured Prediction Models via the Matrix Tree Theorem
... inside-outside algorithm to these mod- els, partition functions and marginals can be com- puted for second-order projective structures, allow- ing log-linear and max-margin training to be ap- plied via the ...
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Tree Structured Data Analysis: AID, CHAID and CART
... Algorithms are available for mixed quantitative and categorical predictors, analogous to analysis of covariance. 2.3 Regression trees Morgan and Sonquist (1963) proposed a simple method for fitting trees to predict a ...
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Models Cascade for Tree Structured Named Entity Detection
... parsing algorithm only the essential infor- mation, since POS tags are directly related to syn- tactic constituents and are sufficient to induce the syntactic structure of a ...
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Structured parallel programming for Monte Carlo Tree Search
... the algorithm is considered as a good target for paralleliza- ...do tree-traversal in parallel along separate paths in the search tree [CWvdH08a, YKK + ...
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