activity
20172022
most citedSimpler Grassmannian optimization

3 citations · 4 across the 6 of their papers we have counts for

collaborators

10 papers

math.OC2022

Simpler flag optimization

Zehua Lai, Lek-Heng Lim, Ke Ye

We study the geometry of flag manifolds under different embeddings into a product of Grassmannians. We show that differential geometric objects and operations -- tangent vector, me…

cs.CC2022

Skew-sparse matrix multiplication

Qiao-Long Huang, Ke Ye, Xiao-Shan Gao

Based on the observation that is isomorphic to a quotient skew polynomial ring, we propose a new method for matrix multiplicat…

math.OC20221 cited

When geometry meets optimization theory: partially orthogonal tensors

Ke Ye, Shenglong Hu

Due to the multi-linearity of tensors, most algorithms for tensor optimization problems are designed based on the block coordinate descent method. Such algorithms are widely employ…

math.OC20203 cited

Simpler Grassmannian optimization

Zehua Lai, Lek-Heng Lim, Ke Ye

There are two widely used models for the Grassmannian , as the set of equivalence classes of orthogonal matrices $\operatorname{O}(n)/(\operatorname{O}(k) \…

math.NA2020

Symmetric Tensor Decompositions On Varieties

Jiawang Nie, Ke Ye, Lihong Zhi

This paper discusses the problem of symmetric tensor decomposition on a given variety : decomposing a symmetric tensor into the sum of tensor powers of vectors contained in .…

math.OC2019

Linear Convergence of an Alternating Polar Decomposition Method for Low Rank Orthogonal Tensor Approximations

Shenglong Hu, Ke Ye

Low rank orthogonal tensor approximation (LROTA) is an important problem in tensor computations and their applications. A classical and widely used algorithm is the alternating pol…