All Research Papers Published In Science China Mathematics

Research Article
2
10.1007/s11425-024-2321-3

Spherically symmetric Einstein-scalar-field equations with potential for wave-like decaying null infinity

Nov 28, 2024
Science China Mathematics
Chuxiao Liu + 1 more +1

Research Article
10.1007/s11425-024-2355-1

Pinching rigidity of minimal surfaces in spheres

Nov 22, 2024
Science China Mathematics
Weiran Ding + 2 more +2

Research Article
13
10.1007/s11425-023-2298-1

Ground states for quasilinear equations of N-Laplacian type with critical exponential growth and lack of compactness

Nov 22, 2024
Science China Mathematics
Sitong Chen + 3 more +3

Research Article
2
10.1007/s11425-023-2194-x

Projective Hilbert modules and sequential approximations

Sep 29, 2024
Science China Mathematics
Lawrence G Brown + 1 more +1

Research Article
2
10.1007/s11425-022-2241-y

Asymptotic false discovery control of the Benjamini-Hochberg procedure for pairwise comparisons

Sep 20, 2024
Science China Mathematics
Weidong Liu + 2 more +2

Research Article
10.1007/s11425-023-2217-2

Byzantine-robust distributed support vector machine

Sep 05, 2024
Science China Mathematics
Xiaozhou Wang + 2 more +2

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Research Article
10.1007/s11425-023-2218-4

Factor-adjusted tests for generalized linear models with multimodal data: An application to breast cancer data

Aug 26, 2024
Science China Mathematics
Dongyu Li + 1 more +1

Research Article
10.1007/s11425-022-2169-9

Noncommutative analysis of Hermite expansions

Jun 28, 2024
Science China Mathematics
Bang Xu

Research Article
2
10.1007/s11425-022-2162-x

Random change point model with an application to the China Household Finance Survey

Jun 24, 2024
Science China Mathematics
Meng Li + 3 more +3

Research Article
4
10.1007/s11425-021-2087-2

Sequential good lattice point sets for computer experiments

Jun 13, 2024
Science China Mathematics
Xue-Ru Zhang + 3 more +3

Sequential Latin hypercube designs have recently received great attention for computer experiments. Much of the work has been restricted to invariant spaces. The related systematic construction methods are inflexible while algorithmic methods are ineffective for large designs. For such designs in space contraction, systematic construction methods have not been investigated yet. This paper proposes a new method for constructing sequential Latin hypercube designs via good lattice point sets in a variety of experimental spaces. These designs are called sequential good lattice point sets. Moreover, we provide fast and efficient approaches for identifying the (nearly) optimal sequential good lattice point sets under a given criterion. Combining with the linear level permutation technique, we obtain a class of asymptotically optimal sequential Latin hypercube designs in invariant spaces where the $L_1$-distance in each stage is either optimal or asymptotically optimal. Numerical results demonstrate that the sequential good lattice point set has a better space-filling property than the existing sequential Latin hypercube designs in the invariant space. It is also shown that the sequential good lattice point sets have less computational complexity and more adaptability.