Reza Parhizkar

IEEE Signal Processing Magazine · 2015

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Reza Parhizkar trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. John C. Gower
2. Kilian Q. Weinberger
3. Raghunandan H. Keshavan
4. I. Borg
5. Josh Tenenbaum

Papers from Reza Parhizkar's perspective

Ordered by how strongly the researchers Reza Parhizkar trusts endorse each paper. Same corpus, a different order for every researcher.

1. A global geometric framework for nonlinear dimensionality reduction.
2. Matrix completion from a few entries
3. Unsupervised Learning of Image Manifolds by Semidefinite Programming (Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.)
4. Modern Multidimensional Scaling: Theory and Applications
5. Multidimensional scaling: I. Theory and method
6. Euclidean Distance Geometry
7. Convex Optimization & Euclidean Distance Geometry
8. Gradient-based learning applied to document recognition
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. ImageNet classification with deep convolutional neural networks

Their papers

• Euclidean Distance Matrices: Essential theory, algorithms, and applications (2015) — 580 citations