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1 - 10 of 13 search results for Economics exam |u:mi.eng.cam.ac.uk where 0 match all words and 13 match some words.
  1. Results that match 1 of 2 words

  2. 8 Aug 2005: exam-ple,by AthitsosandSclaroff for handposeestimation[1] andShakhnarovich et al.
  3. 9 Aug 2005: another. Possible ways to model images include, for exam-ple, creating a set of pixel values, a frequency-based representation composed of Fouriercoefficients, or a grid of binary digits representing the
  4. Contour-Based Learning for Object Detection Jamie ShottonDepartment…

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_iccv05.pdf
    8 Aug 2005: Training examplesEach training image can generate multiple training exam-ples. Each example is a vector of feature responses takenat a particular centroid and is given a binary target value,positive, meaning ... After each round, all training exam-ples
  5. Named Entity Recognition from Speechand Its Use in the ...

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/kim_thesis.pdf
    9 Aug 2005: Named Entity Recognition from Speechand Its Use in the Generation of. Enhanced Speech Recognition Output. Ji-Hwan Kim. Darwin College, University of Cambridge. and. Cambridge University Engineering Department. August 2001. Thesis submitted to the
  6. TODO: This is a placeholder. Final title will be filled later.

    mi.eng.cam.ac.uk/reports/svr-ftp/liao_interspeech05.pdf
    26 Sep 2005: SPLICE [1] is one recent exam-ple of this approach. Alternatively in model-based approaches,the parameters of the system are altered to reflect speech in thenew acoustic environment.
  7. MORTGAGE DEFAULT: CLASSIFICATION TREES ANALYSIS David Feldman* and…

    mi.eng.cam.ac.uk/~mjfg/local/4F10/Feldman_Gross.pdf
    15 Nov 2005: and economics, both theoretically and empirically. Amongst these aspects, mortgage. default has been one of the leading topics.
  8. Parcel:feature subset selectionin variable cost domains M.J.J. Scott, …

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/Scott_tr323.pdf
    9 Aug 2005: distributions. As we increase the number of features, without increasing the number of exam-ples, we create an ever more sparsely populated space.
  9. TWO-WAY CLUSTER VOTING TO IMPROVE SPEAKER DIARISATION PERFORMANCE S.…

    mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp05.pdf
    25 Mar 2005: This reduces the num-ber of all possibleclusterings of the base-segments for this exam-ple from Bell(9) = 21, 147 to 2 Bell(3) = 10.
  10. Article Submitted to Computer Speech and Language Automatic…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/kim_csl04.pdf
    9 Aug 2005: of capitalisation generation are exam-ined for reference word sequences and reference punctuation marks.
  11. 15 Jun 2005: This is best illustrated by exam-ining maximum margin training of a univariate Gaussian class-conditional distribution.

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