Search Results - Artificial Intelligence Constraint Programming String Solving

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  1. 1

    Itemset mining: A constraint programming perspective by Guns, Tias, Nijssen, Siegfried, De Raedt, Luc

    ISSN: 0004-3702, 1872-7921
    Published: Oxford Elsevier B.V 01.08.2011
    Published in Artificial intelligence (01.08.2011)
    “… The approach taken in the field of data mining contrasts with the constraint programming principles developed within the artificial intelligence community…”
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    Journal Article
  2. 2

    StrSolve: solving string constraints lazily by Hooimeijer, Pieter, Weimer, Westley

    ISSN: 0928-8910, 1573-7535
    Published: Boston Springer US 01.12.2012
    Published in Automated software engineering (01.12.2012)
    “… Stand-alone string constraint solving tools, called decision procedures, have been the focus of recent research in this area…”
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    Journal Article
  3. 3

    Twin Support Vector Machines for Pattern Classification by Jayadeva, Khemchandani, R., Chandra, S.

    ISSN: 0162-8828, 2160-9292, 1939-3539
    Published: Los Alamitos, CA IEEE 01.05.2007
    “…We propose twin SVM, a binary SVM classifier that determines two nonparallel planes by solving two related SVM-type problems, each of which is smaller than in a conventional SVM…”
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    Journal Article
  4. 4

    A Simple Algorithm for Solving for the Generalized Longest Common Subsequence (LCS) Problem with a Substring Exclusion Constraint by Zhu, Daxin, Wang, Xiaodong

    ISSN: 1999-4893, 1999-4893
    Published: Basel MDPI AG 01.09.2013
    Published in Algorithms (01.09.2013)
    “…) problem, a generalized LCS problem. For the two input sequences, X and Y , of lengths n andmand a constraint string, P, of length r, the goal is to find the longest common subsequence, Z, of X and Y that excludes P as a substring…”
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    Journal Article
  5. 5

    Soft Margin Multiple Kernel Learning by Xinxing Xu, Tsang, I. W., Dong Xu

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Published: New York, NY IEEE 01.05.2013
    “… Specifically, we introduce an additional slack variable called kernel slack variable to each quadratic constraint of MKL, which corresponds to one support vector machine model using a single base kernel…”
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    Journal Article
  6. 6

    Watermill: An Optimized Fingerprinting System for Databases under Constraints by Lafaye, J., Gross-Amblard, D., Constantin, C., Guerrouani, M.

    ISSN: 1041-4347, 1558-2191
    Published: New York, NY IEEE 01.04.2008
    “… We show two watermarking strategies: an exhaustive one based on integer linear programming constraint solving and a scalable pairing heuristic…”
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    Journal Article
  7. 7

    A One-Layer Recurrent Neural Network With a Discontinuous Hard-Limiting Activation Function for Quadratic Programming by Liu, Q, Wang, J

    ISSN: 1045-9227, 1941-0093
    Published: New York, NY IEEE 01.04.2008
    Published in IEEE transactions on neural networks (01.04.2008)
    “… This neural network is capable of solving a large class of quadratic programming problems. The state variables of the neural network are proven to be globally stable…”
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    Journal Article
  8. 8

    Efficient Dual Approach to Distance Metric Learning by Chunhua Shen, Junae Kim, Fayao Liu, Lei Wang, van den Hengel, Anton

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Published: New York, NY IEEE 01.02.2014
    “… Quadratic Mahalanobis metric learning is a popular approach to the problem, but typically requires solving a semidefinite programming (SDP…”
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    Journal Article
  9. 9

    Novel Maximum-Margin Training Algorithms for Supervised Neural Networks by Ludwig, Oswaldo, Nunes, Urbano

    ISSN: 1045-9227, 1941-0093, 1941-0093
    Published: New York, NY IEEE 01.06.2010
    Published in IEEE transactions on neural networks (01.06.2010)
    “…This paper proposes three novel training methods, two of them based on the backpropagation approach and a third one based on information theory for multilayer…”
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    Journal Article
  10. 10

    New one-versus-all ν-SVM solving intra–inter class imbalance with extended manifold regularization and localized relative maximum margin by Wang, Xuchu, Niu, Yanmin

    ISSN: 0925-2312, 1872-8286
    Published: Amsterdam Elsevier B.V 04.09.2013
    Published in Neurocomputing (Amsterdam) (04.09.2013)
    “… It aims to minimize the scatter of nearby intra-class point pairs while penalize that of nearby inter-class point pairs not being arbitrarily large through the constraints of marginal separation…”
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    Journal Article
  11. 11
  12. 12

    Bounded Strings for Constraint Programming by Scott, Joseph D., Flener, Pierre, Pearson, Justin

    ISBN: 9781479929719, 1479929719
    ISSN: 1082-3409
    Published: IEEE 01.01.2013
    “… We provide a theoretical groundwork for constraint solving on this domain and describe propagation techniques for several common constraints…”
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    Conference Proceeding Journal Article
  13. 13

    BILGO: Bilateral greedy optimization for large scale semidefinite programming by Hao, Zhifeng, Yuan, Ganzhao, Ghanem, Bernard

    ISSN: 0925-2312, 1872-8286
    Published: Amsterdam Elsevier B.V 15.03.2014
    Published in Neurocomputing (Amsterdam) (15.03.2014)
    “… To enable the application of these tasks on a large-scale, scalability and computational efficiency are considered as desirable properties for a practical semidefinite programming algorithm…”
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    Journal Article
  14. 14

    A fast iterative single data approach to training unconstrained least squares support vector machines by Li, Bing, Song, Shiji, Li, Kang

    ISSN: 0925-2312, 1872-8286
    Published: Amsterdam Elsevier B.V 04.09.2013
    Published in Neurocomputing (Amsterdam) (04.09.2013)
    “…Least squares support vector machines (LS-SVMs) express the training in terms of solving a system of linear equations or an equivalent quadratic program (QP…”
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    Journal Article
  15. 15

    Adaptation in Dynamic Environments: A Case Study in Mission Planning by Bui, L. T., Michalewicz, Z., Parkinson, E., Abello, M. B.

    ISSN: 1089-778X, 1941-0026
    Published: New York, NY IEEE 01.04.2012
    “… For example, some tasks might be delayed and/or executed earlier. Some operational constraints can be introduced due to new regulations or business rules…”
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    Journal Article
  16. 16

    Symbolic PathFinder: integrating symbolic execution with model checking for Java bytecode analysis by Păsăreanu, Corina S., Visser, Willem, Bushnell, David, Geldenhuys, Jaco, Mehlitz, Peter, Rungta, Neha

    ISSN: 0928-8910, 1573-7535
    Published: Boston Springer US 01.09.2013
    Published in Automated software engineering (01.09.2013)
    “… Constraints over these expressions are generated from the analysis of different paths through the program…”
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    Journal Article
  17. 17

    Recurrent neural network for approximate nonnegative matrix factorization by Costantini, Giovanni, Perfetti, Renzo, Todisco, Massimiliano

    ISSN: 0925-2312, 1872-8286
    Published: Amsterdam Elsevier B.V 22.08.2014
    Published in Neurocomputing (Amsterdam) (22.08.2014)
    “…A recurrent neural network solving the approximate nonnegative matrix factorization (NMF…”
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    Journal Article
  18. 18

    Predicate Logic as a Modeling Language: Modeling and Solving some Machine Learning and Data Mining Problems with IDP3 by Bruynooghe, Maurice, Blockeel, Hendrik, Bogaerts, Bart, Broes De Cat, De Pooter, Stef, Jansen, Joachim, Labarre, Anthony, Ramon, Jan, Denecker, Marc, Verwer, Sicco

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 28.03.2014
    Published in arXiv.org (28.03.2014)
    “… These research areas have recently shown a strong interest in declarative modeling and constraint solving as opposed to algorithmic approaches…”
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    Paper
  19. 19

    Binary Grey Wolf Optimizer for large scale unit commitment problem by Panwar, Lokesh Kumar, Reddy K, Srikanth, Verma, Ashu, Panigrahi, B.K., Kumar, Rajesh

    ISSN: 2210-6502
    Published: Elsevier B.V 01.02.2018
    Published in Swarm and evolutionary computation (01.02.2018)
    “… The binarization of GWO is owing to the UC problem characteristic binary/discrete search space. The binary string representation of BGWO is analogous to the commitment and de-committed status of thermal units constrained by minimum up/down times…”
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    Journal Article
  20. 20

    Computer Aided Verification: 34th International Conference, CAV 2022, Haifa, Israel, August 7–10, 2022, Proceedings, Part I by Shoham, Sharon, Vizel, Yakir

    ISBN: 3031131851, 9783031131851, 3031131843, 9783031131844
    Published: Cham Springer Nature 2022
    “…This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification,…”
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    eBook