Zobrazeno 1 - 10
of 2 242
pro vyhledávání: '"Wang, Xueqin"'
The exploration of associations between random objects with complex geometric structures has catalyzed the development of various novel statistical tests encompassing distance-based and kernel-based statistics. These methods have various strengths an
Externí odkaz:
http://arxiv.org/abs/2410.18437
The explosion of large-scale data in fields such as finance, e-commerce, and social media has outstripped the processing capabilities of single-machine systems, driving the need for distributed statistical inference methods. Traditional approaches to
Externí odkaz:
http://arxiv.org/abs/2408.17276
Spatiotemporal projections in marine science are essential for understanding ocean systems and their impact on Earth's climate. However, existing AI-based and statistics-based inversion methods face challenges in leveraging ocean data, generating con
Externí odkaz:
http://arxiv.org/abs/2408.01509
Sparsity-constraint optimization has wide applicability in signal processing, statistics, and machine learning. Existing fast algorithms must burdensomely tune parameters, such as the step size or the implementation of precise stop criteria, which ma
Externí odkaz:
http://arxiv.org/abs/2406.12017
Autor:
Wang, Zezhi, Zhu, Jin, Chen, Peng, Peng, Huiyang, Zhang, Xiaoke, Wang, Anran, Zhu, Junxian, Wang, Xueqin
Applying iterative solvers on sparsity-constrained optimization (SCO) requires tedious mathematical deduction and careful programming/debugging that hinders these solvers' broad impact. In the paper, the library skscope is introduced to overcome such
Externí odkaz:
http://arxiv.org/abs/2403.18540
Publikováno v:
Journal of the Royal Statistical Society: Series B, 2024
Parameters of differential equations are essential to characterize intrinsic behaviors of dynamic systems. Numerous methods for estimating parameters in dynamic systems are computationally and/or statistically inadequate, especially for complex syste
Externí odkaz:
http://arxiv.org/abs/2403.14531
The patterns of particulate matter with diameters that are generally 2.5 micrometers and smaller (PM2.5) are heterogeneous in China nationwide but can be homogeneous region-wide. To reduce the adverse effects from PM2.5, policymakers need to develop
Externí odkaz:
http://arxiv.org/abs/2311.02618
Reconstruction of interaction network between random events is a critical problem arising from statistical physics and politics to sociology, biology, and psychology, and beyond. The Ising model lays the foundation for this reconstruction process, bu
Externí odkaz:
http://arxiv.org/abs/2310.09257
Analysis of high-dimensional data has led to increased interest in both single index models (SIMs) and best subset selection. SIMs provide an interpretable and flexible modeling framework for high-dimensional data, while best subset selection aims to
Externí odkaz:
http://arxiv.org/abs/2309.06230
In high-dimensional generalized linear models, it is crucial to identify a sparse model that adequately accounts for response variation. Although the best subset section has been widely regarded as the Holy Grail of problems of this type, achieving e
Externí odkaz:
http://arxiv.org/abs/2308.00251