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13 Mar 2018: li’. 0 200 400 600 800 1000 1200 1400 1600 1800 2000!10! ... 0 200 400 600 800 1000 1200 1400 1600 1800 2000!10!

20 Feb 2018: 0.6 0.8 1 1.2 1.4 1.6 1.8 2150. 200. 250. f0. ... 39 39.5 40 40.5 41 41.5 42140. 160. 180. 200. 220.

3 Jul 2018: Results. # of Clusters 50 100 150 170 200 TextTiling [Hearst 1997] 0.484 DNN-HMM [Yu et.

13 Mar 2018: li’. 0 200 400 600 800 1000 1200 1400 1600 1800 2000!10! ... 0 200 400 600 800 1000 1200 1400 1600 1800 2000!10!

20 Feb 2018: Bearing in mind that the initial parts of. 1The performance deteriorated after 200 dialogues due to an in-crease in speech understanding errors. ... Table 2: Word error rate for different domainsDomain #Adaptation diags #Diags WERSFCore 200 399 15SF1Ext

19 Jan 2018: rate thanthe 200 frames-per-second typical in many sys-tems.

20 Feb 2018: 0. 50. 100. 150. 200. 1 2 3 4 5 6 7 8 9 10 11 12. ... basis. 0. 50. 100. 150. 200. 1 5 9 13 17 21 25 29 33.

14 May 2018: mark edges. 0 200 400 600 800 1000 1200 1400 1600 1800 2000. ... Ker. nel. 0 200 400 600 800 1000 1200 1400 1600 1800 2000.

13 Mar 2018: Images 1 and 5200 0 200. 400. 200. 0. 200. Images 2 and 3. ... 200. Images 4 and 5. Figure8: Imagesof the ellipsesandepipolarlines after convergence.Eachfigure showsthe overlappingof images and , for -GP& 555 # and ¤@@P 555.

13 Mar 2018: 000000. 0"/20. 0. 00#$0. =. 0. $#$0000. 00. ( not! )0#"/200.

13 Mar 2018: Images 1 and 5200 0 200. 400. 200. 0. 200. Images 2 and 3. ... 200. Images 4 and 5. Figure8: Imagesof the ellipsesandepipolarlines after convergence.Eachfigure showsthe overlappingof images and , for -GP& 555 # and ¤@@P 555.

13 Mar 2018: Relative motion of an apparent contour. 118. a. 200-. 150-. 100 -. so •. yS S 50. y S > S 100 •. R/inm / B. / / / A. position error/mm. bB. A. - ... aMO -. 200. 150 •. 100. -2.5 -2.0. 1.5 -1.0 -OS.

20 Feb 2018: 0 200 400 600 800. 50. 55. 60. 65. In-domain InitialisationOut-of-domain Initialisation. ... 0 200 400 600 800. 40. 60. 80. In-domain InitialisationOut-of-domain Initialisation.

13 Mar 2018: 50 100 150 200 250 300 350. 50. 100. 150. 200. ... 200. 250. Figure 3. Examples of the covariances in image 2, for inliersto two motion hypotheses.

13 Mar 2018: 000000. 0"/20. 0. 00#$0. =. 0. $#$0000. 00. ( not! )0#"/200.

20 Feb 2018: 4. -2. 0. 2. 4. 6. 8. 10. 12. 14. 0 200 400 600 800 1000.

20 Feb 2018: As training data, the LEGO corpus [28] is used which con-sists of 200 dialogues (4,885 turns) from the Let’s Go bus infor-mation system [29]. ... Each turnof these 200 dialogues has been annotated with IQ (represent-ing the quality of the dialogue up

20 Feb 2018: 100 200 300 400 500 600 700 8000. 50. 100. 150. ... 200. 250. 300. Time index (ms) of "And then". F0. extr.

20 Feb 2018: 2. 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000.

13 Mar 2018: Relative motion of an apparent contour. 118. a. 200-. 150-. 100 -. so •. yS S 50. y S > S 100 •. R/inm / B. / / / A. position error/mm. bB. A. - ... aMO -. 200. 150 •. 100. -2.5 -2.0. 1.5 -1.0 -OS.

20 Feb 2018: After every batch of 200 training dialogues, the partiallytrained policies were evaluated on1000 simulated dialogues.In the case of theǫ-greedy policy the exploration was switchedoff during the evaluation. ... a pub that has a TV and allows. 100 200 300

20 Feb 2018: This yielded about13K utterances, one for each DA, which is much more difficult than the previous two domains (5.1Kutterances, 200 distinct DAs).

13 Mar 2018: 50 100 150 200 250 300 350. 50. 100. 150. 200. ... 200. 250. Figure 3. Examples of the covariances in image 2, for inliersto two motion hypotheses.

20 Feb 2018: The results are given in Fig. 2. 0 200 400 600 800 1000 1200 1400 1600Training dialogues. ... based adaptation can restore a system tooptimal performance within 200 to 300 adaptationdialogues.

20 Feb 2018: The results indicate that the SL-model couldwork quite well with humans, but was improved byRL on the 200 training dialogues.

20 Feb 2018: 33.5. 34. 34.5. 35. 35.5. 36. 36.5. 37. 37.5. 0 200 400 600 800 1000 1200 1400 1600 1800 2000.

20 Feb 2018: NonNativeA: Chinese sentences 11-20 and 31-40 spoken bythe first 10 native English speakers, 200 utterances in to-tal.

20 Feb 2018: Table 2: Performance of template selection. (p=0.8). Y-clustering (p=0.8)#templates 200 400 600 800 1000 1827.

20 Feb 2018: Usingapproximately 250 linear support vector machine classifiers imple-mented in Java on a Quadcore Pentium 2.4 GHz, each utterance wasparsed in less than 200 ms on average, for both evaluation

15 Jun 2018: The proposed relevance assessment model was implementedin Tensorflow [27]. It consists of 2 BiRNN encoders with400 LSTM recurrent units with hyperbolic tangent (TanH) non-linearities, 200 for the forward states and ... embeddings. Thebinary classifier

15 Jun 2018: 1. 2. 3. 4. 5. 6. 7. 8. 0 100 200 300 400 500 600.

13 Mar 2018: Figure 2:Parallax used to cluster input face images (a). The distributions ofη (1) for the three clusters, computedfrom 200 manually labelled frames is shown in (b). ... 20. 40. 60. 80. 100. 120. (a) (b). 0 100 200 300 400 500 600 700 800 900 10000.

20 Feb 2018: Table 4 Subjective evaluation results. System # Dialogoues # Successful % Success Subjective WER MDP 200 130 65.00 3.37 46.83 POMDP 199 141 70.85 3.22 43.93.

20 Feb 2018: Totrain the policy, the NAC algorithm was executed for 200 iter-ations at a 40% error rate and in each iteration 4000 dialogueswere simulated.

13 Mar 2018: Furthermore, since the size of the ROIs may vary from one videoto the other, the final MGO images are resized to the corresponding refined images withstandard size (which is 200 200 ... 3.2 Dimension Reduction by PCA. In order to reduce the number of

13 Mar 2018: 11, NOVEMBER 1999. 0. 50. 100. 150. 200. 250. tirnc-to-contact (frames). ... upper fp 6.10. lowcr fp. 0 100 200 (C). Fig. 11.

20 Feb 2018: 0 200 400 600 800 1000 1200Dialogues. 30. 20. 10. 0.

13 Mar 2018: 100. 150. 200. 250. 300. 350. 400. a)0 100 200 300 400. ... 0. 50. 100. 150. 200. 250. 300. 350. 400. b). Figure 3: Transfer of points and lines.

20 Feb 2018: 5We ran the grid search over λreg [103,. ,1010],δsim,δant [0,0.1,. ,1.0], k1,k2 [10,25,50,100,200]. ... 100 200 300 400 500 6000. 20. 40. 60. 80. Number of training dialogues.

20 Feb 2018: in-domain 250 3.400.08 62.490.49 9.01 0.05in-domain 500 4.200.08 67.530.47 9.230.04mutual 500 4.600.11 68.080.47 ... 0 50 100 150 200 250 300 350Dialogues. 10. 5. 0.

20 Feb 2018: SFHotelbest prior 9.760.31 88.801.96 7.950.21adapted 10.270.27 92.501.64 8.200.21. three sessions were performed and the results were averaged to ... 0 50 100 150 200 250 300Dialogues. 15. 10. 5. 0.

13 Mar 2018: 400 200 0 200 4000. 0.01. 0.02. 0.03. 0.04. 0.05. 0.06. ... 100 0 100 200 3000. 0.02. 0.04. 0.06. 0.08. x. p(x).

13 Mar 2018: 200 100 0 100 200 300106. 104. 102. Horizontal position (mm).

20 Feb 2018: 150. 200. 250. time (s). F0 (H. z). L2 uv L3 L4uv uvuv L1. ... 0.5 1 1.5 2 2.5 3150. 200. 250. 300. 350. 400.

13 Mar 2018: 200 120 143 200 120 (146) 143 (148) 146.19 (38.1) (128) (146) (15.8). ... For about thegiven number of training samples, using 200 extended regions and 100 weak-learners wouldstart hitting theoretical memory boundaries.

13 Mar 2018: on E. rror. (pi. xel). Hand ball. AdaBoostMCBoostMILSemiOABMCBQ. 100 150 200 250 300 3500. ... ition. Err. or (. pixe. l). Face. AdaBoostMCBoostMILSemiOABMCBQ. 200 400 600 800 1000 12000.

20 Feb 2018: 8. 3 4 5 10 20 50 100. 200. 500. 1000.

13 Mar 2018: 200 120 143 200 120 (146) 143 (148) 146.19 (38.1) (128) (146) (15.8). ... For aboutthe given number of training samples, using 200 extendedregions and 100 weak-learners would start hitting theoreti-cal memory boundaries.

20 Feb 2018: 0 50 100 150 200 250Dialogues. 15. 10. 5. 0. 5.

13 Mar 2018: ìRªi-URÒns«Ð¥]. 0 50 100 150 200 2500.02. 0. 0.02. 0.04. ... 10. 5. 0. 5. 10. 15. 20. #% ,!&. 0 50 100 150 200 2500.1.