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  2. yu.dvi

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/ky_ICASSP06.pdf
    23 Feb 2006: However discriminative training1 has also been exam-ined within this framework [3, 4].
  3. THE CU-HTK MANDARIN BROADCAST NEWS TRANSCRIPTION SYSTEM R. Sinha, ...

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/rs_ICASSP06.pdf
    23 Feb 2006: For exam-ple, the combination of the S2 and S3 GAUSS systems gave a 0.3%and 0.2% absolute improvements oneval03m and eval04 re-spectively.
  4. Multi-Sensory Face Biometric Fusion (for Personal Identification)…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_OTCBVS06.pdf
    19 Mar 2006: W1 was found to be very large). Exam-ples are shown in Fig.
  5. The Layout Consistent Random Field for Recognizing and Segmenting ...

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_cvpr06.pdf
    3 Apr 2006: Second, there are local spatial interac-tions between parts that can help with detection; for exam-ple, we expect to find the nose just above the mouth on aface.
  6. Semi-supervised Learning of Joint DensityModels for Human Pose…

    mi.eng.cam.ac.uk/reports/svr-ftp/navaratnam_semi_supervised.pdf
    14 Sep 2006: The results we show later, and the exam-ples in figure 3 confirm that there is indeed a practical advantage, but it is instructive toconsider on an intuitive level what the
  7. 21 Nov 2006: This is best illustrated by exam-ining maximum margin training of a univariate Gaus-sian class-conditional distribution.
  8. 22 Nov 2006: For exam-ple, the combination of the S2 and S3 GAUSS systems gave a 0.3%and 0.2% absolute improvements oneval03m and eval04 re-spectively.
  9. 22 Nov 2006: It does this by maximising the geometric margin – the dis-tance between the decision boundary and the closest training exam-ples – between classes.
  10. 22 Nov 2006: The output of thismodel is a one-dimensional log-likelihood. To capture thedifferences in generative process between different exam-ples, each example is then mapped to the log-likelihoodgradient-space. ... Consider, for exam-ple, the second derivatives
  11. 22 Nov 2006: 14. 5 Multiple Stream Systems. One standard distributed representation, closely related to the scheme exam-ined here, is multiple stream modeling (20).

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