19 citations · 23 across the 13 of their papers we have counts for
15 papers
On semidefinite descriptions for convex hulls of quadratic programs
Alex L. Wang, Fatma Kilinc-Karzan
Quadratically constrained quadratic programs (QCQPs) are a highly expressive class of nonconvex optimization problems. While QCQPs are NP-hard in general, they admit a natural conv…
Sharpness and well-conditioning of nonsmooth convex formulations in statistical signal recovery
Lijun Ding, Alex L. Wang
We study a sample complexity vs. conditioning tradeoff in modern signal recovery problems (including sparse recovery, low-rank matrix sensing, covariance estimation, and abstract p…
Hidden convexity, optimization, and algorithms on rotation matrices
Akshay Ramachandran, Kevin Shu, Alex L. Wang
This paper studies hidden convexity properties associated with constrained optimization problems over the set of rotation matrices . Such problems are nonconvex due t…
Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation
Jiali Wang, Wen Huang, Rujun Jiang +2
The Stackelberg prediction game (SPG) is popular in characterizing strategic interactions between a learner and an attacker. As an important special case, the SPG with least square…
Accelerated first-order methods for a class of semidefinite programs
Alex L. Wang, Fatma Kilinc-Karzan
This paper introduces a new storage-optimal first-order method (FOM), CertSDP, for solving a special class of semidefinite programs (SDPs) to high accuracy. The class of SDPs that…
Implicit regularity and linear convergence rates for the generalized trust-region subproblem
Alex L. Wang, Yunlei Lu, Fatma Kilinc-Karzan
In this paper we develop efficient first-order algorithms for the generalized trust-region subproblem (GTRS), which has applications in signal processing, compressed sensing, and e…