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Table 3: MAE and ROC-4 area of two CF algorithms, \Item averages quot; and \User averages quot;, in MovieLens. Note that the ROC-4 area is meaningless when \User averages quot; is used because for a certain user all items will receive the same prediction. CF algorithms MAE ROC-4

in Deriving Private Information from Randomly Perturbed Ratings
by unknown authors
"... In PAGE 7: ... 6.1 MovieLens Table3 rst gives the prediction and recommendation accuracy of two naive CF algorithms, \Item averages quot; and \User averages quot;; they are consid- ered as the baselines for future comparisons. Since both algorithms are based on the sum operation, it is easy to design privacy-preserving schemes for them.... ..."

Table 3: MAE and ROC-4 area of two CF algorithms, \Item averages quot; and \User averages quot;, in MovieLens. Note that the ROC-4 area is meaningless when \User averages quot; is used because for a certain user all items will receive the same prediction. CF algorithms MAE ROC-4

in Deriving Private Information from Randomly Perturbed Ratings
by unknown authors
"... In PAGE 7: ... 6.1 MovieLens Table3 rst gives the prediction and recommendation accuracy of two naive CF algorithms, \Item averages quot; and \User averages quot;; they are consid- ered as the baselines for future comparisons. Since both algorithms are based on the sum operation, it is easy to design privacy-preserving schemes for them.... ..."

Table 2: Selected Results

in ABSTRACT
by Yanchang Zhao, Longbing Cao
"... In PAGE 4: ... For each group of customers, the association rules of de- mographics and quick/moderate/slow payers are discovered using association mining algorithms. Some selected results are shown in Table2 . Note that the real benefit type codes are replaced with AAA, BBB or CCC in all tables in this paper for privacy preserving.... ..."

Table 3: Comparison of HMM, HMM/poly 2 (2nd degree), and HMM/poly 3 (3rd degree). HMM HMM/poly 2 HMM/poly 3

in Using Polynomial Networks For Speech Recognition
by W. M. Campbell, C. C. Broun
"... In PAGE 8: ... A compar- ison of the standard approach and the new method is shown in Table 3. From Table3 , we can see that the HMM/polynomial combination performs well for all menus, but is not dramatically better than the standard Baum-Welch training for quadratic polynomials. We were somewhat disappointed by this result, since for the case of speaker verification, the new method of training has definite ad- vantages in accuracy and computation, see [2, 4].... In PAGE 8: ... We experimented using the log scoring technique instead of the sum technique shown in (6). When the probability was not allowed to go below BCBMBCBD, we obtained similar results to those shown in Table3 . Experimenting with choices other than BCBMBCBD did not drastically change the results.... ..."
Cited by 1

Table 2: Forward computation of full slices.

in ABSTRACT Experimental Evaluation of Using Dynamic Slices for Fault Location ∗
by Xiangyu Zhang, Haifeng He, Neelam Gupta, Rajiv Gupta
"... In PAGE 4: ... If s is an assignment, then the full slice for each of the variable whose definition is generated by s is assigned the slice and the statement s itself. Forward computation of full slices for execution in case of Error 2 is shown in Table2 . We can see that the faulty statement (10) is in the full slice but not in the data slice of z at 141.... ..."

Table 5.3.2.1: Forward-only HMM simulation result

in Keywords: Hidden Markov Models, Semi-Hidden Markov Models, Fading Channels, Error Source Modeling Markov Modeling of Third Generation Wireless Channels
by Ihsan A. Akbar, Brian D. Woerner, Jeffrey H. Reed, Ihsan A. Akbar 2003

TABLE IV Forward mapping for image computation.

in Interval Diagrams for Efficient Symbolic Verification of Process Networks
by Karsten Strehl, Lothar Thiele

Table 3: Overall confusion matrix with HMM.

in Human posture tracking and classification through stereo vision
by Stefano Pellegrini, Luca Iocchi 2006
"... In PAGE 7: ...igure 3: People sitting on a chair (non-occluded vs. occluded). good behavior of the system in recognizing postures in presence of partial occlusions, that are typical for example during office-like activities. Finally, Table3 presents the total confusion matrix of all the experiments performed. The presence of no errors in the LAID posture is given by the fact that the height of the person from the ground is the most dis- criminant measure and this is reliably computed by stereo vision, while the ON KNEE posture is very dif- ficult because it relies on tracking the feet, which is very noisy and unreliable with the stereo tracker we have used.... ..."
Cited by 1

Table 1. Forward computation of slices. dynamic dynamic static

in Efficient Forward Computation of Dynamic Slices Using Reduced Ordered Binary Decision Diagrams
by Xiangyu Zhang, Rajiv Gupta 2004
"... In PAGE 3: ... Algorithm 1 Updating Slicing Information Procedure Update(a33 ) 1: a34a36a35a37a33a39a38a41a40 = a42a36a33a19a43 ; 2: a44a19a33a39a45a46a40a48a47 a33a50a49 = a44a19a33a39a45a46a40a26a34a51a44a53a52a54a45a56a55 ++; 3: for (each use a57 in a58a59a34a60a40a11a47 a33a50a49 ) do 4: a34a36a35a37a33a39a38a41a40 = a34a36a35a37a33a39a38a41a40a62a61a64a63a48a40a66a65 a34a60a35a67a33a21a38a51a40a11a47 a57a68a49 ; 5: end for 6: a63a11a38a51a63 = the statement a34 in a69a59a70a71a47 a33a39a49 which has the maximum a44a19a33a39a45a46a40a48a47 a34a51a49 value; 7: a34a36a35a37a33a39a38a41a40 = a34a36a35a37a33a39a38a41a40a72a61a46a34a36a35a37a33a39a38a41a40a11a47 a63a11a38a51a63a73a49a21a47 a35a74a40a36a33a75a47 a63a11a38a76a63a73a49a77a49 ; 8: a34a36a35a37a33a39a38a41a40a11a47 a33a50a49a78a47 a35a74a40a36a33a75a47 a33a50a49a79a49 = a34a36a35a37a33a39a38a41a40 ; 9: a35a74a40a36a33a75a47 a33a39a49 ++; 10: for (each definition a63 in a70a14a40a66a65a80a47 a33a50a49 ) do 11: a63a48a40a66a65 a34a36a35a37a33a39a38a41a40a11a47 a63a73a49 = a34a36a35a37a33a39a38a51a40 ; 12: end for Forward computation of dynamic slices for example in Fig. 1 is shown in Table1 . In the execution step of a20a34a17a81a2 , which is a0a82a30a83a10 a20 a85a84a39a86 a11 a76a87 a11 a76a0a3a88 , a0 is defined, a4 a86 a11 a76a87 a11 a76a0a89a5 are the variables that are used.... ..."
Cited by 18

Table 1. Forward computation of slices. dynamic dynamic static

in Efficient Forward Computation of Dynamic Slices Using Reduced Ordered Binary Decision DIagrams
by Xiangyu Zhang, Rajiv Gupta, Youtao Zhang 2004
"... In PAGE 3: ... Algorithm 1 Updating Slicing Information Procedure Update(a33 ) 1: a34a36a35a37a33a39a38a41a40 = a42a36a33a19a43 ; 2: a44a19a33a39a45a46a40a48a47 a33a50a49 = a44a19a33a39a45a46a40a26a34a51a44a53a52a54a45a56a55 ++; 3: for (each use a57 in a58a59a34a60a40a11a47 a33a50a49 ) do 4: a34a36a35a37a33a39a38a41a40 = a34a36a35a37a33a39a38a41a40a62a61a64a63a48a40a66a65 a34a60a35a67a33a21a38a51a40a11a47 a57a68a49 ; 5: end for 6: a63a11a38a51a63 = the statement a34 in a69a59a70a71a47 a33a39a49 which has the maximum a44a19a33a39a45a46a40a48a47 a34a51a49 value; 7: a34a36a35a37a33a39a38a41a40 = a34a36a35a37a33a39a38a41a40a72a61a46a34a36a35a37a33a39a38a41a40a11a47 a63a11a38a51a63a73a49a21a47 a35a74a40a36a33a75a47 a63a11a38a76a63a73a49a77a49 ; 8: a34a36a35a37a33a39a38a41a40a11a47 a33a50a49a78a47 a35a74a40a36a33a75a47 a33a50a49a79a49 = a34a36a35a37a33a39a38a41a40 ; 9: a35a74a40a36a33a75a47 a33a39a49 ++; 10: for (each definition a63 in a70a14a40a66a65a80a47 a33a50a49 ) do 11: a63a48a40a66a65 a34a36a35a37a33a39a38a41a40a11a47 a63a73a49 = a34a36a35a37a33a39a38a51a40 ; 12: end for Forward computation of dynamic slices for example in Fig. 1 is shown in Table1 . In the execution step of a20a34a17a81a2 , which is a0a82a30a83a10 a20 a85a84a39a86 a11 a76a87 a11 a76a0a3a88 , a0 is defined, a4 a86 a11 a76a87 a11 a76a0a89a5 are the variables that are used.... ..."
Cited by 18
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