### Table 2. Competitive ratios given in this paper.

2005

Cited by 6

### TABLE 2. Hidden functions of the Isw2 complex revealed by direct competition of double mutants with single mutants

### Table 1. Lower bounds on the competitive ra- tio of on-line algorithms, depending on the platform type and on the objective function.

2006

"... In PAGE 3: ....1 while in another one (task T on P3) it will be, say, 1.2. Clearly, the minimum of the performance ratios over all ex- ecution scenarios is the desired bound on the competitive ratio of the algorithm: no algorithm can do better than this bound! Because we have three platform types (communication- homogeneous, computation-homogeneous, fully heteroge- neous) and three objective functions (makespan, max-flow, sum-flow), we have nine bounds to establish. Table1 sum- marizes the results, and shows the influence on the platform type on the difficulty of the problem. As expected, mixing both sources of heterogeneity (i.... In PAGE 13: ...ing algorithms. The major contribution of this paper lies on the theoretical side, and is well summarized by Table1 . We have provided a comprehensive set of lower bounds for the competitive ratio of any deterministic scheduling algorithm, for each source of heterogeneity and for each target objec- tive function.... ..."

Cited by 1

### Table 2. Competitiveness and Potential Value, Realized Value and Overall Gains DECLINE IMPROVE ODDS RATIO COMPETITION

"... In PAGE 5: ...WISE 2006 Extended Abstract 5 Our results support all three competition-related hypotheses in Table2 . Highly-competitive industries have higher managerial and selection pressures.... ..."

### Table 2. Product Competitiveness measures

2003

"... In PAGE 76: ... The overall framework was analyzed by importance of the performance criteria. Table2 lists measures used in the case model for each Product Competitiveness criteria. External performance references were available for all except quality measures (not included into the case model).... ..."

### Table 1. Best competitive ratios in P quot; for COUNTER and RANDOM RESET.

1994

"... In PAGE 12: ...4. Table1 shows, for various d, the best competitive ratio for COUNTER(k,{k - 1)) guaranteed by Theorem 3.... In PAGE 12: ... [20] is true for the list update problem. It is possible to find RANDOM RESET algorithms which do slightly better than the COUNTER competitive ratios given in Table1 . These results are also shown in Table 1.... In PAGE 12: ...onjecture of Manasse et al. [20] is true for the list update problem. It is possible to find RANDOM RESET algorithms which do slightly better than the COUNTER competitive ratios given in Table 1. These results are also shown in Table1 . The best resetting distributions we have found all have the property that the counter is reset to either the largest or the second largest possible value.... In PAGE 12: ... The best resetting distributions we have found all have the property that the counter is reset to either the largest or the second largest possible value. Table1 also lists, for various d, the best k, the best competitive ratio, and the probability of resetting to k. Notice, however, that while all COUNTER algorithms use O(n) random bits regardless of the length of the request sequence, these random resetting algorithms use Qm) random bits for a request sequence of length m.... ..."

Cited by 43

### Table 1: Values for a and the corresponding upper bound for the competitive ratio.

"... In PAGE 21: ..., and continue with identifying the next extension. Appendix C: Computing the Competitive Ratio For an illustration, Table1 shows the competitive values that strategy SCANSEARCH achieves for ak = a. For computing these estimates, we compare the numerous cases of strategy SCANSEARCH with the op- timum, resulting in the values listed in Tables 2 and 3.... ..."

### Table 1. The competitive ratio of symmetric and asymmetric routing problems.

2005

"... In PAGE 2: ... Previous work, both theoretical and experimental, has focused on the off-line version [7,10,13]. Our results are summarized in Table1 , where they are also compared with the known results for the symmetric case. As we will see, the asymmetric TSP is substantially harder than the normal TSP even when considered from an on-line point of view; in other words, OL-ATSP is not a trivial extension of OL-TSP.... In PAGE 2: ... As we will see, the asymmetric TSP is substantially harder than the normal TSP even when considered from an on-line point of view; in other words, OL-ATSP is not a trivial extension of OL-TSP. In fact, as Table1 shows, most bounds on the competitive ratio are strictly higher than the corresponding bounds for OL-TSP, and in particular in the nomadic case there cannot be on-line algorithms with a constant competitive ratio. Although our algorithms come essentially from the symmetric case, they require some adjustment in order to attain useful competitive ratios.... ..."

Cited by 5

### Table 3. Summary of theoretical results algorithm competitive ratio partitioning bound

1997

"... In PAGE 23: ... We also show how several speci c Experts-DTF algorithms can be applied to the MTS setting, and introduce and analyze several new variations. Their bounds are summarized in Table3 . As a special case of our results, we show how the basic randomized Weighted-Majority algorithm can be used for the problem of combining on-line algorithms on-line.... ..."

Cited by 32

### Table 3. Summary of theoretical results algorithm competitive ratio partitioning bound

1997

"... In PAGE 23: ... We also show how several speci c Experts-DTF algorithms can be applied to the MTS setting, and introduce and analyze several new variations. Their bounds are summarized in Table3 . As a special case of our results, we show how the basic randomized Weighted-Majority algorithm can be used for the problem of combining on-line algorithms on-line.... ..."

Cited by 32