5 citations · 11 across the 8 of their papers we have counts for
8 papers
The landscape of deterministic and stochastic optimal control problems: One-shot Optimization versus Dynamic Programming
Jihun Kim, Yuhao Ding, Yingjie Bi +1
Optimal control problems can be solved via a one-shot (single) optimization or a sequence of optimization using dynamic programming (DP). However, the computation of their global o…
Virtual Network Embedding without Explicit Virtual Network Specification
Jiangnan Cheng, Yingjie Bi, Ao Tang
Network virtualization enables Internet service providers to run multiple heterogeneous and dedicated network architectures for different customers on a shared substrate. In existi…
Sharp Restricted Isometry Property Bounds for Low-rank Matrix Recovery Problems with Corrupted Measurements
Ziye Ma, Yingjie Bi, Javad Lavaei +1
In this paper, we study a general low-rank matrix recovery problem with linear measurements corrupted by some noise. The objective is to understand under what conditions on the res…
General Low-rank Matrix Optimization: Geometric Analysis and Sharper Bounds
Haixiang Zhang, Yingjie Bi, Javad Lavaei
This paper considers the global geometry of general low-rank minimization problems via the Burer-Monterio factorization approach. For the rank- case, we prove that there is no s…
Local and Global Linear Convergence of General Low-rank Matrix Recovery Problems
Yingjie Bi, Haixiang Zhang, Javad Lavaei
We study the convergence rate of gradient-based local search methods for solving low-rank matrix recovery problems with general objectives in both symmetric and asymmetric cases, u…
Global and Local Analyses of Nonlinear Low-Rank Matrix Recovery Problems
Yingjie Bi, Javad Lavaei
The restricted isometry property (RIP) is a well-known condition that guarantees the absence of spurious local minima in low-rank matrix recovery problems with linear measurements.…
On Upper Bounding Shannon Capacity of Graph Through Generalized Conic Programming
Yingjie Bi, Ao Tang
The Shannon capacity of a graph is an important graph invariant in information theory that is extremely difficult to compute. The Lovasz number, which is based on semidefinite prog…
Refined Shapley-Folkman Lemma and Its Application in Duality Gap Estimation
Yingjie Bi, Ao Tang
Based on concepts like kth convex hull and finer characterization of nonconvexity of a function, we propose a refinement of the Shapley-Folkman lemma and derive a new estimate for…