J
Jun Sun
Researcher at Stanford University
Publications - 4
Citations - 298
Jun Sun is an academic researcher from Stanford University. The author has contributed to research in topics: Eigenvalues and eigenvectors & Semidefinite programming. The author has an hindex of 3, co-authored 3 publications receiving 287 citations.
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Journal ArticleDOI
The Fastest Mixing Markov Process on a Graph and a Connection to a Maximum Variance Unfolding Problem
TL;DR: A dual of the FMMP problem is formulated and it is shown that it has a natural geometric interpretation as a maximum variance unfolding (MVU) problem, the problem of choosing a set of points to be as far apart as possible, measured by their variance, while respecting local distance constraints.
Journal ArticleDOI
Fastest mixing markov chain on a path
TL;DR: This note proves that fastest mixing is obtained when each edge has a transition probability of 1/2, and considers symmetric transition probabilities, meaning those that satisfy Pi j = Pji, which is a symmetric, stochastic, tridiagonal matrix.
Proceedings ArticleDOI
A duality view of spectral methods for dimensionality reduction
Lin Xiao,Jun Sun,Stephen Boyd +2 more
TL;DR: A unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenmaps, and maximum variance unfolding is presented.
Journal ArticleDOI
Invalidity of “Smaller is stronger” size effect due to stress-induced nanoscale α″ and ω phases in metastable Ti2448
TL;DR: In this article , the authors showed that the nanoscale phase transitions induced by high-level flow stress (∼1GPa) during Ti-24Nb-4Zr-8Sn pillar deformation are invalidated by the Smaller is Stronger effect.