### Table 3.1: Resource augmentation results for the weighted a0 a1 norms of flow time.

2003

Cited by 6

### Table 1: Resource augmentation results for the stan- dard average QoS algorithms.

### Table 3.1: Resource augmentation results for the weighted COD4 norms of flow time.

### Table 1: PN (the probability of necessary causation) as a function of assumptions and available data. ERR stands of the excess-risk-ratio 1 ? P (yjx0)=P (yjx) and CERR is given in Eq. (49). The non-entries (|) represent vacuous bounds, that is, 0 P N 1. Assumptions Data Available

2000

"... In PAGE 24: ...6 Summary of results We now summarize the results from Section 4 that should be of value to practicing epidemiologists and policy makers. These results are shown in Table1 , which lists the best estimand of PN under various assumptions and various types of data|the stronger the assumptions, the more informative the estimates. We see that the excess-risk-ratio (ERR), which epidemiologists commonly identify with the probability of causation, is a valid measure of PN only when two assumptions can be ascertained: exogeneity (i.... In PAGE 25: ...concerned with associations between such factors and susceptibility to expo- sure, as is often assumed in the literature [Khoury , 1989, Glymour, 1998]. The last two rows in Table1 correspond to no assumptions about exo- geneity, and they yield vacuous bounds for PN when data come from either experimental or observational study. In contrast, informative bounds (25) or point estimates (49) are obtained when data from experimental and ob- servational studies are combined.... ..."

Cited by 5

### Table 1 The upper and lower bounds of s and standard form II.

### Table4: FractionsofErrorsandSVs,AlongwiththeMarginsofClassSeparation, for the Toy Example Depicted in Figure 11.

### Table 5 Kolmogorov-Smirnov with Lilliefors significance correction

### Table Bounds

1996

Cited by 5

### Table 1: Upper and lower bounds on (Kn) established in this paper.

2000

"... In PAGE 10: ... We have established upper bounds and lower bounds on the geometric thickness of complete graphs. Table1 contains the upper and lower bounds on (Kn)forn 100. Many open questions remain about geometric thickness.... In PAGE 10: .... Find exact values for (Kn) (i.e., remove the gap between upper and lower bounds in Table1... ..."

Cited by 25

### Table 2 Sets of 20 correlated problems (maximization)

2005

"... In PAGE 8: ... Again solutions were obtained rapidly and were near-optimal. The results in Table2 exhibit much of the same features as those in Table 1. Both sets of results significantly improved on those in Wilson [4], which used the same problem instances, where run times were longer and optimality levels poorer.... ..."