Xiucai Ding
Statistics and Probability · 2016–2020
A researcher in the Science corpus: 4 papers; trusts 56 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 117 citations into it; #9,557 of 12,932 by trust here, #10,855 by citations
- Mathematical Physics — 71 citations into it
- Discrete Mathematics and Combinatorics — 44 citations into it
- Artificial Intelligence — 14 citations into it
- Economics and Econometrics — 14 citations into it
- Probabilistic & Bayesian Methods — 13 citations into it
- Geometry and Topology — 10 citations into it
- Statistical Learning Theory — 10 citations into it
Whom Xiucai Ding trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Antti Knowles
- A. Onatski
- L. Erdős
- Jun Yin
- Iain M. Johnstone
- Natesh S. Pillai
- Noureddine El Karoui
- Horng-Tzer Yau
- Florent Benaych-Georges
- Alex Bloemendal
Who trusts Xiucai Ding overall
Papers from Xiucai Ding's perspective
Ordered by how strongly the researchers Xiucai Ding trusts endorse each paper. Same corpus, a different order for every researcher.
- Eigenvalues of large sample covariance matrices of spiked population models
- On the distribution of the largest eigenvalue in principal components analysis
- ASYMPTOTICS OF SAMPLE EIGENSTRUCTURE FOR A LARGE DIMENSIONAL SPIKED COVARIANCE MODEL
- Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
- Tracy–Widom limit for the largest eigenvalue of a large class of complex sample covariance matrices
- DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES
- Finite sample approximation results for principal component analysis: a matrix perturbation approach
- Random Matrices
- Central limit theorems for eigenvalues in a spiked population model
- The Largest Eigenvalue of Rank One Deformation of Large Wigner Matrices
Their papers
- Spiked separable covariance matrices and principal components (2019) — 70 citations
- Singular vector and singular subspace distribution for the matrix denoising model (2018) — 60 citations
- Statistical inference for principal components of spiked covariance matrices (2020) — 56 citations
- A necessary and sufficient condition for edge universality at the largest singular values of covariance matrices (2016) — 58 citations