### Table 4. Low Rank Approximation by Partition

2006

Cited by 5

### Table 7. Regression analysis of contract design: separating research firms with high and low reputation underwriters High Rank Low Rank High Rank Low Rank Pooled

2007

"... In PAGE 32: ... In other words, the high rank of their underwriter should reduce the uncer- tainty about their type and render the termination and broader access rights more dispensable. In Columns 1 and 2 of Table7 , we find that the effects are instead larger and significant only among research firms with the highly ranked underwriters. The result is robust to the inclu- sion of year and firm fixed effects (Columns 3 and 4), though the significance of the coefficient estimate of interest in the high-rank sample diminishes.... ..."

### Table 39. The efficiency of the transcription system in the first, low rank, test sample.

"... In PAGE 54: ...roduced transcriptions with an error rate of only 1.7%. This is not surprising since 80% of the transcriptions generated by Twol were obtained from the internal lexicon. If the lexical lookup transcriptions are separated from the generated ones the error rates shown in Table39 are obtained. Table 39.... ..."

### Table 2: Inexact Newton method. AT KA is a low-rank downdate of AT A.

2000

"... In PAGE 17: ... Outer will refer to inexact Newton (IRLS) iterations and inner to PCGLS iterations. The maximum number of down- dates is set to 20 for all the results in Table2 , 3, 4, and 5. Thus the actual downdates q is less than or equal to 20.... In PAGE 18: ...3. in Table2 for the Talwar function show that we terminate by the maximum number of PCGLS iterations allowed, t = 40, at all iterations, for stocfor2 when AT A and AT KA are used as preconditioners, and for maros when AT A is used as a preconditioner. This suggests that we should increase q and or t so that the linear system can be solved to high accuracy.... In PAGE 18: ... This suggests that we should increase q and or t so that the linear system can be solved to high accuracy. The results in Table2 and 3 suggest that the Fair function is performing better than other functions on inexact Newton method. The results in Table 4 and 5 show that on average the Fair function is doing better than other functions on IRLS method.... In PAGE 18: ... The Logistic function is doing almost as good as the Fair function on IRLS method. Comparing the results in Table2 and 3 with the results in Table 4 and 5 we see that Newton method converges faster than IRLS method, and the low-rank downdates do not lead to a signi cant decrease in the inexact Newton (IRLS) iterations carried out (outer). Thus... ..."

Cited by 4

### Table 2: Inexact Newton method. AT KA is a low-rank downdate of AT A.

"... In PAGE 15: ... Outer will refer to inexact Newton (IRLS) iterations and inner to PCGLS iterations. The maximum number of downdates is set to 20 for all the results in Table2 , 3, 4, and 5. Thus the actual downdates q is less than or equal to 20.... In PAGE 15: ...n Theorem 3.2. We will base our analysis on the values of outer and inner. The results in Table2 for the Talwar function show that we terminate by the maximum number of PCGLS iterations allowed, t = 40, for stocfor2 when AT A and AT KA are used as preconditioners, and for maros when AT A is used as a preconditioner. This suggests that we should increase q and or t.... In PAGE 15: ... This suggests that we should increase q and or t. The results in Table2 and 3 suggest that the Fair function is performing better than other functions on inexact Newton method. The results in Table 4 and 5 show that on average the Fair function is doing better than other functions on IRLS method.... In PAGE 15: ... The Logistic function is doing almost as good as the Fair function on IRLS method. Comparing the results in Table2 and 3 with the results in Table 4 and 5 we see that Newton method converges faster than IRLS method, and the low-rank downdates do not lead to a significant decrease in the inexact Newton (IRLS) iterations carried out (outer). Thus it is worthwhile to... ..."

### Table 3: Number of iterations varying the dimension of the low-rank update with W = V quot;.

2002

"... In PAGE 6: ... For the experiments shown in Table 2, we use a left preconditioner and the formulation described in Proposition 1 that is W H = UH quot; M1. Similar results are displayed in Table3 using the formulation described in Proposition 2 that is with W = V quot;. In this latter case, the cost for the eigencomputation to setup the update is halved because only right eigenvectors need to be computed.... ..."

Cited by 10

### Table 6: Number of CG iterations varying the dimension of the low-rank update.

2002

"... In PAGE 9: ...pdate presented in Proposition 5. As a preconditioner we use IC(t) [17]. We observe a similar improvement for SPD linear systems to what was seen in the previous section. This is illustrated in Table6 where we show the number of CG iterations as we vary the dimension of the positive semi-de nite update. To show that the improvement of the update is not too closely related to the quality of the initial preconditioner we show, for BCSSTK27 and S1RMQ4M1, the number of iterations for two di erent thresholds for IC.... ..."

Cited by 10

### Table 3.6: Number of CG iterations varying the dimension of the low-rank update.

2002

Cited by 10

### Table 3: Inexact Newton method. AT KA is a low-rank downdate of AT A.

2000

Cited by 4

### Table 5: Inexact IRLS method. AT KA is a low-rank downdate of AT A.

2000

Cited by 4