### Table I. Numerical results for reduction into a block-semiseparable matrix of semiseparability rank 2

2004

### Table 1: A representational decomposition

2002

"... In PAGE 3: ... Second, the significant interaction between the cue type (landmark vs object) and the array type (fixed vs shifted) was surprising. The reaction time in the shifted-object condition was significantly longer than that in any other conditions (the RT in the shifted-object condition was about 1800ms, 2100ms, and 2700ms longer than that in the fixed- object, shifted-landmark, and fixed-landmark conditions, respectively, see also Table1 ), indicating some additional operations occurred in that condition. An analysis of the computational differences among conditions sheds light on what these operations could be.... In PAGE 4: ...representations/operations for each condition is summarized in Table1 . It seems that the race model explains the RT data reasonably well.... ..."

Cited by 1

### Table 4: Ambiguity for the non-hierarchical representation.

"... In PAGE 27: ... shared the same representation in terms of micro-patterns with a di erent pattern in our sample. The results are shown in Table4 . The table also compares two possible variations of specifying larger units in terms of smaller building blocks.... ..."

### Table 2. Performances for ulv, flv, flu, fbu, ulp and ubp on tight programs. The problems pre- sented are the same as in Table 1.

"... In PAGE 9: ... Otherwise, when using simple backtracking failed-literal helps in general in improving performances, avoiding (with a forward rea- soning) the visit of useless parts of the search tree that otherwise (due to the absence of L ) the solver would explore (the results are confirmed by some smaller experiments on 4-coloring problems not shown here). In Table2 , there are the results on tight programs when using CMODELS2 with a non-static heuristic. For randomly generated logic programs (18-20), using a non- static heuristic in general helps for increasing the performances.... In PAGE 10: ... Even more, now it leads to negative results, with a huge difference when using heuristic P . Rows (21-34) in Table2 are results for tight real-world logic programs.... ..."

### Table(2) A comparison of symmetric sparse solver and Cholesky decomposition

### Table 7. Computational complexity of updating methods (based on the use of Householder transformations) without recomputing the ULV decomposition of a new L matrix. The number M(G) is the number of ops required to compute a matrix-vector product Gx or yTG.

1996

"... In PAGE 23: ... Hence, rank-revealing techniques are not required for the ULV decomposition of matrices B, C, and . Table7 contains the complexities (ignoring lower order terms) for folding-in terms and documents, and the three phases of ULV-updating. From these complexities the required number of oating-point operations (or ops) for each method can be compared for varying numbers of added documents or terms.... In PAGE 23: ...10) re ects that of the original m n term-by-document matrix A with m n, then folding-in will still require considerably fewer ops than ULV-updating when adding p new documents provided p n. Figure 8 illustrates the number of oating-point operations (log-scale) required (using the expressions from Table7 ) to update the last p = 25; 50; 75 abstracts to the collection of MEDLINE abstracts represented by the 285 (100 ? p) sparse term-by-document matrix previously discussed in Section 2.... ..."

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### TABLE IV SPEED-UPS AND EFFICIENCIES OF STRIP DECOMPOSITION PARALLELIZATION ALGORITHM OF FAST DIRECT POISSON SOLVER FOR TEST GRID M1

in Strip Decomposition Parallelization of Fast Direct Poisson Solver on a 3D Cartesian Staggered Grid

### Table 3 Computation time comparisons show that our BEM solver is significantly faster than a FD solver. This FD solver implements a fast sparse solver in an adaptive gridding sense [2].

### Table 2: Table of Decompositions

1993

"... In PAGE 6: ... 6). Table2 summarizes all of the decompositions of a polyhedron. 3 Representation of Polyhedra 3.... ..."

Cited by 89