### Table 1: Fraction of random subset sum problems solved by a particular re- duction algorithm applied to bases L and L0, respectively.

1992

"... In PAGE 14: ... When one uses known algorithms for lattice basis reduction, applying them to lattice L0 instead of lattice L also yields dramatic improvements, although the results are not as good as they would be in the presence of a lattice oracle. For example, Table1 presents the comparison obtained in one particular set of experiments. The lattices used were not exactly L and L0, and the reduction algorithm used a combination of ideas from several sources.... ..."

Cited by 57

### Table 1: Fraction of random subset sum problems solved by a particular re- duction algorithm applied to bases L and L0, respectively.

1992

"... In PAGE 14: ... When one uses known algorithms for lattice basis reduction, applying them to lattice L0 instead of lattice L also yields dramatic improvements, although the results are not as good as they would be in the presence of a lattice oracle. For example, Table1 presents the comparison obtained in one particular set of experiments. The lattices used were not exactly L and L0, and the reduction algorithm used a combination of ideas from several sources.... ..."

Cited by 57

### Table 1. Fraction of random subset sum problems solved by a particular reduction algorithm applied to bases L and Lprime, respec- tively.

1992

"... In PAGE 14: ... are not as good as they would be in the presence of a lattice oracle. For example, Table1 presents the comparison obtained in one particular set of experiments. The lattices used were not exactly L and Lprime, and the reduction algorithm used a combination of ideas from several sources.... ..."

Cited by 57

### Table 1: Fraction of random subset sum problems solved by a particular reduction algorithm applied to bases L and L0, respectively.

"... In PAGE 6: ... When one uses known algorithms for lattice basis reduction, applying them to lattice L0 instead of lattice L also yields dramatic improvements, although the results are not as good as they would be in the presence of a lattice oracle. For example, Table1 presents the comparison obtained in one particular set of experiments. The lattices used were not exactly L and L0, and the reduction algorithm used a combination of ideas from several sources.... In PAGE 6: ... More extensive data sets and details of the computations are presented in [14]. For each entry in Table1 , n denotes the number of items, and b the number of bits... ..."

### Table I: Time used for solving continuous problem. Average of 100 instances Uncorrelated Weakly corr. Subset-sum Zig-zag

1996

Cited by 1

### Table I: Time used for solving the continuous problem (in seconds), where entries are rounded to two decimal digits. Average of 100 instances Uncorrelated Weakly corr. Subset-sum Zig-zag

1996

Cited by 1

### Table 4. Subset sum data sets.

2003

"... In PAGE 13: ... So far, we have left out comparisons regarding the choice of the objective according to SSS. Table4 shows the results obtained for a collection of very different test sets generated with SSS. Two facts stand out: first, a comparison with Table 1 shows, that the SSS instances are much easier to solve than for other choices of the objective.... ..."

Cited by 10

### Table 4. Subset sum data sets.

2003

"... In PAGE 13: ... So far, we have left out comparisons regarding the choice of the objective according to SSS. Table4 shows the results obtained for a collection of very different test sets generated with SSS. Two facts stand out: first, a comparison with Table 1 shows, that the SSS instances are much easier to solve than for other choices of the objective.... ..."

Cited by 10

### Table 2. Execution times for parallel subset- sum problem

"... In PAGE 6: ...2GHz AMD Opteron machine. Table2 shows the real-time results. As expected, gcc -O2 is the fastest but Cuckoo is slightly slower than unoptimized gcc.... ..."

### Table 2. Execution times for parallel subset- sum problem

"... In PAGE 6: ...2GHz AMD Opteron machine. Table2 shows the real-time results. As expected, gcc -O2 is the fastest but Cuckoo is slightly slower than unoptimized gcc.... ..."