### Table 3: E ect of the circulation scheme on the performance of the light contribution com- putation phase (Phase 4).

1996

"... In PAGE 22: ... As is seen in Table 2, the loosely-coupled circulation scheme on simple ring topology achieves almost the same high e ciency values as the demand-driven scheme in spite of the fact that the demand-driven scheme exploits the rich hypercube topology and the direct-routing facility of iPSC/2. Table3 illustrates the execution times of the distributed light contribution computations (Phase 4) during a single iteration of the parallel algorithm. The last column of Table 3 illustrates the percent decrease in the parallel execution time obtained by using the contri- bution vector circulation scheme instead of the form-factor vector circulation scheme.... ..."

Cited by 1

### Table 4: Classi cation accuracy comparisons for DIvote and distributed boosting. Dataset DIvote Distributed Boosting (Lazarevic and Obradovic, 2002) Pendigits 96.4% 96.5%

"... In PAGE 19: ... We learned an ensemble of CC classi ers by running 100 iterations of DIvote with a bite size of 800 for each of the datasets. Table4 reports the accuracies achieved by DIvote and distribtued boosting on the separate testing sets. We report the distributed boosting accuracy for the \Simple Majority quot; voting scheme using p = 0 directly from (Lazarevic and Obradovic, 2002).... ..."

### Table 2: Payments with Different Rules in the Simple Problem.

2001

"... In PAGE 4: ... Example. In Table2 we compare the payments made with each payment scheme in our simple problem. Notice that neither the Large or Small schemes provide useful guidance about how to distribute the discount across the two sellers, this depends on how the tie is broken.... ..."

Cited by 54

### Table 1: Comparisons between 5 MCMC methods run for 10 million iterations on a simple example.

1994

"... In PAGE 6: ... The actual posterior distribution is known and all methods gave a correct estimate for the mean and standard deviation of the posterior to several decimal places if allowed to run for long enough. Table1 shows the times it takes to run each of the ve methods for 10 million iterations. For the MH methods the tuning constants were xed to give an acceptance rate of approximately 45% which appeared to give optimal results (see Gelman, Roberts and Gilks (1995) for a mathematical explanation of this), and for this acceptance rate we list the e ciency.... ..."

Cited by 1

### Table 4. The impact of various net distribution schemes with best algorithm for detailed pin distribution.

"... In PAGE 6: ... The results show that DPD achieves the lowest wirelength for all circuits, while also decreasing the number of layers. In Table4 , we study how the number of routing layers and wirelength (WL) change with various Net Distribution approaches. We used very simple heuristics such as assigning all i-nets to the routing interval above its floorplan (RUP) and below its floorplan (RD).... ..."

### Table 3. Simple types defined by the Scheme module

2004

"... In PAGE 5: ....2.1 Additional Types The Scheme module, like the C part, revolves mainly around types. First, there are several simple types that are implemented in the Scheme module, summarized in Table3 . Adding these types is sim- ple, as described in Section 3.... ..."

Cited by 6

### Table 3. Simple types defined by the Scheme module

2004

"... In PAGE 70: ....2.1 Additional Types The Scheme module, like the C part, revolves mainly around types. First, there are several simple types that are implemented in the Scheme module, summarized in Table3 . Adding these types is sim- ple, as described in Section 3.... ..."

### Table 3. Simple types defined by the Scheme module

"... In PAGE 5: ....2.1 Additional Types The Scheme module, like the C part, revolves mainly around types. First, there are several simple types that are implemented in the Scheme module, summarized in Table3 . Adding these types is sim- ple, as described in Section 3.... ..."

### Table 2. Distribution of iterations

2002

"... In PAGE 9: ... With regard to existing workflow-models the iteration structure is capsuled in a so called Complex Activity, that means it is embedded in an activity-structure, which in turn contains a workflow-graph itself and additionally the iter- ations probability information: In analogy to duration histograms, the iteration histogram L of a complex activity is a binary relation of n rows (p; x) (probability p and iteration count x). Table2 shows a possible iteration histogram L. This matrix can be produced empirically from statistical analysis of the work-... ..."

Cited by 5

### Table 2. Distribution of iterations

2002

"... In PAGE 9: ... With regard to existing workflow-models the iteration structure is capsuled in a so called Complex Activity, that means it is embedded in an activity-structure, which in turn contains a workflow-graph itself and additionally the iter- ations probability information: In analogy to duration histograms, the iteration histogram L of a complex activity is a binary relation of n rows (p; x) (probability p and iteration count x). Table2 shows a possible iteration histogram L. This matrix can be produced empirically from statistical analysis of the work-... ..."

Cited by 5