Showing 1 - 20 results of 313 for search '"discrimination learning"', query time: 0.38s Refine Results
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    Unifying generative and discriminative learning principles by Strickert Marc, Posch Stefan, Grau Jan, Keilwagen Jens, Grosse Ivo

    Published 2010-02-01
    “…Only recently it was noticed that discriminative learning principles can be superior over generative ones in diverse bioinformatics applications, too.…”
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    Auditory Discrimination Learning: Role of Working Memory. by Yu-Xuan Zhang, David R Moore, Jeanne Guiraud, Katharine Molloy, Ting-Ting Yan, Sygal Amitay

    Published 2016-01-01
    “…Here we present three lines of evidence from healthy adults in support of the idea that the enhanced transfer of auditory discrimination learning is mediated by working memory (WM). …”
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    Dorsolateral Striatum Engagement Interferes with Early Discrimination Learning by Hadley C. Bergstrom, Anna M. Lipkin, Abby G. Lieberman, Courtney R. Pinard, Ozge Gunduz-Cinar, Emma T. Brockway, William W. Taylor, Mio Nonaka, Olena Bukalo, Tiffany A. Wills, F. Javier Rubio, Xuan Li, Charles L. Pickens, Danny G. Winder, Andrew Holmes

    Published 2018-05-01
    “…These data provide further evidence suggesting that the DLS is recruited in the construction of stimulus-elicited actions that ultimately automate behavior and liberate cognitive resources for other demands, but with a cost to performance at the outset of learning. : What is the contribution of the DLS in early discrimination learning? Bergstrom et al. show using in vivo optogenetics, fluorescence in situ hybridization, and brain-wide activity mapping that silencing the DLS facilitates early discrimination learning, drives activity in a parallel PL-DMS circuit, and preferentially recruits the DLS “direct” output pathway. …”
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    Global discriminative learning for higher-accuracy computational gene prediction. by Axel Bernal, Koby Crammer, Artemis Hatzigeorgiou, Fernando Pereira

    Published 2007-03-01
    “…With genomic information being created at an ever-increasing rate, it is worth investigating alternative approaches in which many different types of genomic evidence, with complex statistical dependencies, can be integrated by discriminative learning to maximize annotation accuracy. Among discriminative learning methods, large-margin classifiers have become prominent because of the success of support vector machines (SVM) in many classification tasks. …”
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