The Relaxed Online Maximum Margin Algorithm
Maximum Margin Clustering
... finding maximum mar- gin hyperplanes through ...be relaxed to a soft-clustering formulation which can be feasibly solved with a semidef- inite ...our maximum margin clustering technique often ...
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Learning from Images with Captions Using the Maximum Margin Set Algorithm
... Abstract—A large amount of images with accompanying text captions are available on the Internet. These are valuable for training visual classifiers without any explicit manual intervention. In this paper, we present a ...
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A unified lexical processing framework based on the Margin Infused Relaxed Algorithm. A case study on the Romanian Language
... The previously proposed methods vary from rule-based to data-driven and different authors employ different classifiers (in data-driven approaches), such as Maximum Entropy Classifiers, Classification and ...
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Relevant gene subset selection: the maximum margin criterion in SVM and genetic algorithm
... Specifically, this thesis extends the classic Support Vector Machine (SVM) algorithm to present a new hill- climbing method Relevant Subset Selection Using The Maximu[r] ...
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Maximum Margin Algorithms with Boolean Kernels
... the maximum margin algorithm with the Boolean kernels, giving negative results for several settings of the ...the maximum margin algorithm can overfit even when learning simple ...
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Relaxed Online SVMs for Spam Filtering
... 4.3 Discussion The comparison results shown in Tables 5, 6, and 7 are striking in two ways. First, they show that the performance of Online SVMs can be matched and even exceeded by re- laxed margin methods. ...
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Constant Rate Approximate Maximum Margin Algorithms
... CRAMMA algorithm on this data set is astonishingly good, beyond any ...the maximum margin in the limit R β → ∞) we decided to present the ones obtained for the parameter values = 1 and η 1 for which ...
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Laplacian Maximum Margin Criterion for Image Recognition
... Table 1 and Table 2 show the experimental results of different algorithms on the COIL20 and PIE database respectively. Figure 2 plots the recognition accuracy of seven methods vs. number of projection vectors on the PIE ...
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Orthogonal Maximum Margin Projection for Face Recognition
... new algorithm, called orthogonal maximum margin projection(OMMP) which is fundamentally based on the maximum margin ...the margin between embeddings belong to different classes, ...
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Maximum Relative Margin and Data-Dependent Regularization
... the maximum margin setting and have also shown empirical improvements over SVMs (Jaakkola et ...basic maximum margin formulation that are similar in spirit to those the RMM ...batch ...
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MedLDA: Maximum Margin Supervised Topic Models
... when online users post their reviews for products or restaurants, they usually associate each review with a rating score or a thumb-up/thumb-down opinion; web sites or pages in the pub- lic Yahoo! Directory 1 can ...
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Boosting as a Regularized Path to a Maximum Margin Classifier
... The boosting idea was first introduced by Freund and Schapire (1995), with their AdaBoost algorithm. AdaBoost and other boosting algorithms have attracted a lot of attention due to their great success in data ...
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A new technique for maximum load margin estimation and prediction
... Based on the literature reviews, ANN, PSO and GA are the most common methods used by the former researchers to determine the maximum load margin (MLM) of a system. On the other hand, the application of AIS ...
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Approximate Maximum Margin Algorithms with Rules Controlled by the Number of Mistakes
... 5 Conclusions We presented MICRA, a family of Perceptron-like large margin classifiers com- pletely independent of the length of the weight vector. Our theoretical approach proved sufficiently powerful in ...
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An open source tool for negation detection: a maximum margin approach
... learning algorithm, the in- ternal data representation and the set of features used to represent the negation ...the maximum-margin CRF scope model – exper- imenting with different features, sequence ...
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A New Approximate Maximal Margin Classification Algorithm
... the maximum output ofthese classifiers. Again, margin is defined as the difference between the output ofthe classifier associated with the correct label and the output ofany other ...
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Online Learning of Relaxed CCG Grammars for Parsing to Logical Form
... learning algorithm in our approach can learn weights for the new rules, effectively allowing the model to learn to use them only in appropriate contexts; in the exper- iments we show that the rules are highly ...
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Online Budgeted Maximum Coverage
... arrive online, where each set S i is given by the elements that it contains, as well as its cost, c(S i ...the online algorithm has to decide whether to accept it or to reject it, under the ...
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Orthogonal maximum margin projection subspace for radar target HRRP recognition
... small sample size problem. B. Li et al. [33] propose the locally linear discriminant embedding (LLDE) method. LLDE apply the constrained weights to strengthen the classification ability. Y. Chen et al. [34] present a ...
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Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision
... 4.3 Practical Considerations Although the learning algorithm of MMRN is sim- ple and general, the quality of the learned model is dictated by the effectiveness of the search proce- dure. Increasing the beam size ...
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