### Table 6: Restricting the search for the first longest common substring (underlined).

"... In PAGE 7: ... This both prevents the algorithm from assigning the same target region to two source columns and also diminishes the run-time for the task. Table6 graphically represents the matrix of operations for com- paring instance henry to rhwarner from Table 1, where the target has been masked to remove regions already covered by the partial translation formula. In this case, two possible recipes are present and both substrings have the same length; thus we select the left-most, or earliest occurring, recipe as indicated, leading to the refined translation formula %first[1-1]last[1-n].... ..."

### Table 4. Speedup achieved for each of the three repeated substring search strategies

2003

"... In PAGE 8: ... A more detailed account of our search algorithm and the results obtained is in preparation [10]. We ran the three distributed algorithms over the aforementioned laboratory of 90 clients and recorded the speedup data shown in Table4 . For these computations we did not have sole use of the laboratory.... ..."

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### Table 1. Speedup achieved for each of the three repeated substring search strategies

2003

"... In PAGE 8: ... A more detailed account of our search algorithm and the results obtained is in preparation [10]. We ran the three distributed algorithms over the aforementioned laboratory of 90 clients and recorded the speedup data shown in Table1 . For these computations we did not have sole use of the laboratory.... ..."

Cited by 5

### Table 1. Speedup achieved for each of the three repeated substring search strategies.

2002

"... In PAGE 5: ... A more detailed account of these results is in preparation [10]. We ran the three distributed algorithms over the aforementioned laboratory of 90 clients and recorded the speedup data shown in Table1 . For these computations we did not have sole use of the laboratory.... ..."

Cited by 1

### Table 1. Speedup achieved for each of the three repeated substring search strategies.

2002

"... In PAGE 4: ... A more detailed account of our bioinformatics results is in preparation [8]. We ran the three distributed algorithms over the aforementioned laboratory of 90 clients and recorded the speedup data shown in Table1 . For these computations we did not have sole use of the laboratory.... ..."

Cited by 1

### Table 1 MAX{DICUT: Mean number of satis ed clauses with standard deviation. OB is the oblivious search, NOB the non{oblivious one, see text for details.

1999

"... In PAGE 11: ... OB is the oblivious search, NOB the non{oblivious one, see text for details. Table1 summarizes the mean number of satis ed clauses obtained by sim- ple Local Search algorithms, using either the oblivious (LS-OB) or the non- oblivious (LS-NOB) function. The main result is that the NOB Local Search does lead to local optima of a better average quality with respect to OB.... In PAGE 11: ... This result con rms what has been found in (8) for the case of the usual disjunctive SAT problem. Better local optima are found if OB Local Search starts from a local optimum of NOB (line NOB amp; OB in Table1 ), and still better ones if 10 n additional iterations of LS+ are allowed (the best move is accepted even if it leads to worse function values). By considering the dependence on the density, let us note that the relative im- provement (clauses satis ed by LS-NOB minus clauses satis ed by LS-OB, divided by clauses satis ed by LS-OB) of the average number of clauses sat- is ed by LS-OB and LS-NOB decreases for larger densities, ranging from approximately 0.... ..."

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### Table 1: MAX-DICUT: Mean number of satis ed clauses with standard deviation. OB is the oblivious search, NOB the non{oblivious one, see text for details.

"... In PAGE 7: ... OB is the oblivious search, NOB the non{oblivious one, see text for details. Table1 summarizes the mean number of satis ed claused obtained by simple local search algorithm, using either the oblivious (LS-OB) or the non-oblivious (LS-NOB) function. The main result is that the NOB local search does lead to local optima of a better average quality with respect to OB.... In PAGE 7: ... This result con rms what has been found in [8] for the case of the usual disjunctive SAT problem. Better local optima are found if OB local search starts from a local optimum of NOB (line NOB amp;OB in Table1 ), and still better ones if 10 n additional iterations of LS+ are allowed (the best move is accepted even if it leads to worse function values). By considering the dependence on the density, let us note that the relative improvement of the average number of clauses satis ed by LS-OB and LS-NOB decreases for larger densities, passing from approximately 0.... ..."

### Table 1: MAX-3{SAT: Mean number of unsatis ed clauses (statistical error in parenthesis when available). The rst ve lines are from Hansen-Jaumard, GSAT+ is from Selman et. al. OB is the oblivious search, NOB the non{oblivious one, see text for details.

1997

"... In PAGE 7: ...hen available). The rst ve lines are from Hansen-Jaumard, GSAT+ is from Selman et. al. OB is the oblivious search, NOB the non{oblivious one, see text for details. Table1 summarizes a previous comparison executed in [7] for MAX-3-SAT tasks. The average number of unsatis ed clauses at the local optimum is listed with its statistical error in parenthesis.... ..."

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### Table 4. Search and update performance for the synthesized architecture.

"... In PAGE 9: ... Parameter Set Block RAMs Slices B 276 (57%, 4968 KBits) 13950 (30%) D 254 (52%, 4572 KBits) 14274 (31%) 6.3 Performance Table4 shows the performance of search and update operations for the synthesized pipelined architecture in terms of millions of operations per second (MOPS). Search pipeline depth is also reported.... ..."

### Table 1: MAX-3{SAT: Mean number of unsatis ed clauses (statistical error in parenthesis when available). The rst ve lines are from Hansen-Jaumard, GSAT+ is from Selman et. al. OB is the oblivious search, NOB the non{oblivious one, see text for details.

1997

"... In PAGE 7: ... If b r is a measured average quantity for a task obtained by the 10 runs with di erent random seeds, the default standard deviation is that of b r with respect to task variation. Table1 summarizes a previous comparison executed in [7] for MAX-3-SAT tasks. The average number of unsatis ed clauses at the local optimum is listed with its statistical error in parenthesis.... ..."

Cited by 22