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  • Features, techniques and evaluation in predicting articles . . .
    Abstract Robust findings of citations have a positive impact on researchers and significantly con-tribute to academic development As a paper is cited more frequently or used as a refer-ence in other articles, its citation count increases Papers with higher citations tend to be more influential than those less cited Research on predicting citation counts has evolved throughout the year in
  • Repetitive Action Counting With Motion Feature Learning
    Abstract Repetitive action counting aims to count the number of repetitive actions in a video The critical challenge of this task is to uncover the periodic pattern between repetitive actions by computing feature similarity between frames However, existing methods only rely on the RGB feature of each frame to compute the feature similarity while ne-glecting the background change of
  • 2003-2007 Outlook - LIPA
    Scorecard Performance – Project Based Metric Deliverables Delivered and LIPA Reviewing (Various Stages) PSEG LI to Submit Prior to March 31
  • Reducing the CNOT count for Cli ord+T circuits on NISQ . . .
    In this paper we consider the problem of reducing the CNOT-count in Cli ord+T circuits on connectivity constrained architectures such as noisy intermediate-scale quantum (NISQ) [Pre18] computing devices We \slice" the circuit at the position of Hadamard gates and \build" the intermediate portions We investigated two kinds of partitioning - (i) a simple method of parti-tioning the gates of
  • Microsoft Word - LiCheung2013ClassifierAcquisition. docx
    L1 Acquisition of Classifiers Count-Mass Distinction (Mandarin) In numerical classifier languages, such as Mandarin, classifiers are morphemes that occur next to numerals and “classify” nouns on some semantic basis (see entry on Classifiers) For example, ‘three cats’ in Mandarin requires the classifier zhī 隻, which is typically used with nouns for animals (sān zhī māo
  • Learning that classifiers count: Mandarin-speaking children’s . . .
    Learning that classifiers count: Mandarin-speaking children’s acquisition of sortal and mensural classifiers
  • Lecture 10: Recurrent Neural Networks - Stanford University
    Vanilla RNN Gradient Flow Bengio et al, “Learning long-term dependencies with gradient descent is difficult”, IEEE Transactions on Neural Networks, 1994 Pascanu et al, “On the difficulty of training recurrent neural networks”,


















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