J. Cadima
Computational Mechanics · with Jolliffe · 2001–2018
A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 7 citations into it
- Statistics and Probability — 6 citations into it
- Analytical Chemistry — 5 citations into it; #212 of 1,254 by trust here, #626 by citations
- Computer Vision and Pattern Recognition — 5 citations into it
Whom J. Cadima trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts J. Cadima overall
- Hooman Latifi
- Ian T. Jolliffe
- Barbara Koch
- Nickolay T. Trendafilov
- Lorraine Rupande
- Shipeng Wang
- Rung Ching Chen
- Wen-Tao Wu
- Mudassir Uddin
Papers from J. Cadima's perspective
Ordered by how strongly the researchers J. Cadima trusts endorse each paper. Same corpus, a different order for every researcher.
- A Modified Principal Component Technique Based on the LASSO
- Analysis of a complex of statistical variables into principal components.
- Economic inequality and burden-sharing in the provision of local environmental quality
- On Consistency and Sparsity for Principal Components Analysis in High Dimensions (Journal of the American Statistical Association)
- A Direct Formulation for Sparse PCA Using Semidefinite Programming (SIAM Review)
- A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. (Biostatistics)
- LIII. On lines and planes of closest fit to systems of points in space
- Robust principal component analysis?
- Statistical Learning with Sparsity: The Lasso and Generalizations
- A Framework for Robust Subspace Learning (International Journal of Computer Vision)
Their papers
- Variable selection and the interpretation of principal subspaces (2001) — 117 citations
- Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes (2018) — 57 citations
- Principal component analysis: a review and recent developments (2016) — 9,010 citations