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31 - 40 of 243 search results for KaKaoTalk:po03 op where 0 match all words and 243 match some words.
  1. Results that match 1 of 2 words

  2. robust.dvi

    mi.eng.cam.ac.uk/~sjy/papers/heyo04.pdf
    20 Feb 2018: 4.2 Log-Linear Interpolation. Log-linear interpolation has been applied to languagemodel adaptation and has been shown to be equivalentto a constrained minimum Kullback-Leibler distance op-timisation problem(Klakow,
  3. The Effect of Cognitive Load on a Statistical Dialogue ...

    mi.eng.cam.ac.uk/~sjy/papers/gtht12.pdf
    20 Feb 2018: 4.4 Conversational patterns. Given that the subjects felt the change of cognitiveload when they were talking to the system and op-erating the car simulator at the same time, we
  4. POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN…

    mi.eng.cam.ac.uk/~sjy/papers/gmsv15.pdf
    20 Feb 2018: 5]. Here, we address the problem ofdecision-making. Moving from a limited domain dialogue system that op-erates on a relatively modest ontology to an open domain. ... 5. EXPERIMENTAL SET-UP. In order to examine the ability of the proposed method to
  5. 20 Feb 2018: the Q-function estimatewe expect during the process of learning and H is a linear op-erator that captures the reward lookahead from the Q-function(see Eq.
  6. 20 Feb 2018: Thisprovides increased robustness to errors in speechunderstanding and automatic dialogue policy op-timisation via reinforcement learning (Roy et al.,2000; Zhang et al., 2001; Williams and Young,2007; Young et al.,
  7. gasic_acltslp.dvi

    mi.eng.cam.ac.uk/~sjy/papers/gayo11.pdf
    20 Feb 2018: actions. The policy op-timisation is performed in interaction with a simulated user which gives a reward to the systemat the end of every dialogue.
  8. A HIERARCHICAL ATTENTION BASED MODEL FOR OFF-TOPIC SPONTANEOUSSPOKEN…

    mi.eng.cam.ac.uk/~mjfg/ALTA/publications/ASRU2017/HierarchicalAttentionBased/hierarchical-attention-based.pdf
    24 Jan 2018: The HATMalso contains an additional 200-dimensional BiLSTM prompt-searchencoder. The ATM was trained for 5 epochs with the Adam op-timizer [19], an exponentially decaying learning rate with an
  9. Ghostscript wrapper for C:\Documents and Settings\mike\My…

    mi.eng.cam.ac.uk/~cipolla/publications/invitedTalk/2003-MOS-handtracking.pdf
    13 Mar 2018: Hand Tracking Using A Quadric Surface Model. R. Cipolla1 B. Stenger1 A. Thayananthan1 P. H. S. Torr2. 1 University of Cambridge, Department of Engineering, Trumpington Street,Cambridge, CB2 1PZ, UK. 2 Microsoft Research Ltd., 7 J J Thomson Ave,
  10. Large scale labelled video data augmentation for semantic…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2017-ICCV-label-propagation.pdf
    13 Mar 2018: However, in contrast to image classification and somedeep learning lead problems of computer vision, semanticsegmentation (especially for autonomous driving) still op-erates on limited size datasets which do not exceed 5000labelled
  11. Refining Architectures of Deep Convolutional Neural Networks Sukrit…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2016-CVPR-refining-CNN.pdf
    13 Mar 2018: Please see Fig 1 for an illustration ofthese operations. We do not consider the other plausible op-erations for architectural refinement of CNN; for instance,arbitrary connection patterns between two layers ... 2. We introduce a strategy that starts with

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