14 citations · 25 across the 5 of their papers we have counts for
5 papers · 1 filter
An Optimal High-Order Tensor Method for Convex Optimization
Bo Jiang, Haoyue Wang, Shuzhong Zhang
This paper is concerned with finding an optimal algorithm for minimizing a composite convex objective function. The basic setting is that the objective is the sum of two convex fun…
A Unified Adaptive Tensor Approximation Scheme to Accelerate Composite Convex Optimization
Bo Jiang, Tianyi Lin, Shuzhong Zhang
In this paper, we propose a unified two-phase scheme to accelerate any high-order regularized tensor approximation approach on the smooth part of a composite convex optimization mo…
Structured Quasi-Newton Methods for Optimization with Orthogonality Constraints
Jiang Hu, Bo Jiang, Lin Lin +2
In this paper, we study structured quasi-Newton methods for optimization problems with orthogonality constraints. Note that the Riemannian Hessian of the objective function require…
On decompositions and approximations of conjugate partial-symmetric complex tensors
Taoran Fu, Bo Jiang, Zhening Li
Conjugate partial-symmetric (CPS) tensors are the high-order generalization of Hermitian matrices. As the role played by Hermitian matrices in matrix theory and quadratic optimizat…
Highly accurate model for prediction of lung nodule malignancy with CT scans
Jason Causey, Junyu Zhang, Shiqian Ma +6
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It rem…