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  2. The Effect of Cognitive Load on a Statistical Dialogue ...

    mi.eng.cam.ac.uk/~sjy/papers/gtht12.pdf
    20 Feb 2018: The averaged results are givenin Table 2. We performed a Kruskal test, followedby pairwise comparisons for every scenario for eachanswer and all differences are statistically signifi-cant (p < 0.03) apart
  3. nips7.dvi

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2005-ANIPS-Williams-VIC-algorithm.pdf
    13 Mar 2018: This is restrictive in practicein that test data may contain distortions that take it outside the strict ambit of the trainingpositives. ... This can be computed in terms of likelihoods. (1)so then the test becomes (2)where.
  4. DEEP-CARVING: Discovering Visual Attributes by Carving Deep Neural…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2015-CVPR-Shankar.pdf
    13 Mar 2018: M}. For a test image xt, the task is to predictyt A, i.e. ... The vali-dation set and the test set contain 2104 and 2967 imagesrespectively.
  5. Gesture Recognition Under Small Sample Size Tae-Kyun Kim1 and ...

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2007-ACCV-Kim.pdf
    13 Mar 2018: High dimensional inputspace and a small training set often cause over-fitting of classifiers to the training data and poorgeneralization to new test data. ... 3. Nevertheless, the twointersection sets of the train and test sets are stillplaced in the
  6. Robust Instance Recognition in Presence ofOcclusion and Clutter Ujwal …

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2014-ECCV-3D-recognition.pdf
    13 Mar 2018: We capture six test scenes with the same five objects. Eachtest scene has 400 500 frames containing multiple objects with different back-grounds/clutter and poses.Scenario 4: This scenario tests ... Recall. Pre. cis. ion. LineModSupp. SIterative(Edge).
  7. 20 Feb 2018: Bold values are statis-tically significant compared to non-bold values in the same groupusing an unpaired t-test with p < 0.01. ... The difference between bold valuesand non-bold values is statistically significant using an unpaired t-test where p < 0.02.
  8. TPAMI-0554-0706-2 1..14

    mi.eng.cam.ac.uk/~cipolla/publications/article/2007-PAMI-Kim.pdf
    13 Mar 2018: We used 18 randomlyselected training/test combinations of the sequences forreporting identification rates. ... The test recognition rates changed byless than 1 percent for all of the different trials of randompartitioning.
  9. 20 Feb 2018: During test-ing, we greedily selected the most probable intention andapplied beam search with the beamwidth set to 10 when de-coding the response. ... The significance test is based on atwo-tailed student-t test, between NDM and LIDMs.
  10. Learning to Track with Multiple Observers Björn StengerComputer…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2009-CVPR-hand-tracking.pdf
    13 Mar 2018: The running of tests consisting of all possible combina-tions of all trackers on all test sequences would take a pro-hibitive amount of time to complete. ... In order to test the validity of such a setup, weperformed tests using the complete tracking
  11. 20 Feb 2018: 2016a). Statisticalsignificance was computed using two-tailed Wilcoxon Signed-Rank Test ( p <0.05) to compare models w/and w/o snapshot learning. ... 0.540 0.559 0.459. Table 2: Average activation of gates on test set.

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