Global score metric based structure learning
Influence modelling and learning between dynamic bayesian networks using score-based structure learning
... of learning the structure of a dynamic Bayesian network, the prob- lem is considered in the complete and incomplete data ...in learning the dynamic Bayesian network structure for complete ...
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Multi-task learning with a natural metric for quantitative structure activity relationship learning
... We have analysed the results of our work further by identifying what drug target classes benefited from the proposed MTL QSAR. We define a fully benefited class as an L5 class in which all drug targets have better ...
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Multi-task learning with a natural metric for quantitative structure activity relationship learning
... tree based structure and learning was performed at different levels of the ...transfer learning and MTL were used to predict the binding of the Major Histocompatibility Complex (MHC)-I ...
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Metric Learning for Graph Based Domain Adaptation
... graph structure involving both instances and features for transfer learning, while we focus on domain adaptation and use homogeneous graph consisting of instance nodes ...
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Metric Learning for Graph-Based Domain Adaptation
... graph structure involving both instances and features for transfer learning, while we focus on domain adaptation and use homogeneous graph consisting of instance nodes ...
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Polyhedral aspects of score equivalence in Bayesian network structure learning
... structural learning of these ...ILP-based learning decomposable models, but they used different binary encodings of the ...restricted learning was the goal in both these papers unlike in this ...
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Maximum Metric Score Training for Coreference Resolution
... Ng (2005) proposed a ranking model to maxi- mize F-measure during testing. In the approach, n different coreference outputs for each test text are generated, by varying four components in a coref- erence resolution ...
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A Metric for Sentence Ordering Assessment Based on Topic-Comment Structure
... Figure 1: Correlation between w t t , w c t , w t c , w c c & accuracy In Table 1, O, R, R1 and R2 refer to the initial sentence order and the permutations described above and O > /< /= R• shows the proportion of times ...
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A Joint Local and Global Deep Metric Learning Method for Caricature Recognition
... deep metric unit, aiming to learn a similarity metric adap- tive to local feature ...the metric learning part, while the loss is still cross-entropy ...the structure of metric ...
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Content Based Image Retrieval by Supervised Metric Learning
... We base our area descriptors of every individual VOI on a 3-D adaptation of the arrangement of elements utilized as a part of Sluimer et al. [7], which was appropriate for lung surfaces portrayal. The components are ...
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Learning a Metric during Hierarchical Clustering based on Constraints
... 5.2 Evaluation Measures We used two measures to evaluate and compare the perfor- mance of our algorithms. First, we used the F-score gained in accordance to the given dataset, which is supposed to be the true ...
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Metric learning for incorporating privileged information in prototype-based models
... MZE and MAE test results 2 , along with standard deviations over 20 training /test re-samplings, are listed in Tables. 4.3 and 4.4, respectively 3 . We use bold face to indicate the lowest average error value among the ...
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Learning Entailment Relations by Global Graph Structure Optimization
... graph learning problem, and searched for the best graph under a global transitivity ...one score-based and the other probabilistic, and we have shown that under certain conditions (specified in ...
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Revit Structure 2014 Fund METRIC
... Autodesk ® Revit ® Structure 2014 Fundamentals - Metric Revision 1.0 ASCENT - Center for Technical Knowledge is a division of RAND Worldwide Inc., providing custom developed knowledge products and services ...
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Attention-Based Deep Metric Learning for Near-Duplicate Video Retrieval
... Traditional NVDR methods aggregate frame-level features into video-level representation using Global Vector (GV) [11] and Bag-of-Words (BoW) [20]. GV averages frame-level fea- tures, treating every frame equally, ...
Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning
... the Global Covariance Pooling tries to explore a second- order pooling (covariance pooling) in ...as global image ...pooling based methods (Lin, RoyChowdhury, and Maji 2015; Gao et ...
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Metric Learning for Structured Data
... the global optimum is already found in the first optimization step and will not change ...lGMMs based on LVQ models because these models feature a crisp assignment of Gaussians to labels leading to a lot of ...
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Two-stage metric learning
... the learning instances varies significantly between different ...neighborhood structure of a learning instance normalized by a ”scaling” factor, the sum of similarities of the learning ...
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Coordinated Local Metric Learning
... By learning a Mahalanobis metric over this embedding, we simultaneously learn local metrics for each cluster, and also obtain an alignment of the local ...
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Adaptive Learning of Local Semantic and Global Structure Representations for Text Classification
... Adaptive learning at corpus ...adaptive learning strategy, the weights are learned based on the whole ...and structure information vary according to the sentence ...in structure ...
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