In this article, we have provided general, comprehensive coverage of the SDR technique,
from its practical deployments and scope of applicability to key theoretical results. We have …

This paper proves that nonconvex quadratically constrained quadratic programs can be
solved in polynomial time when their underlying graph is acyclic, provided the constraints …

Online influence maximization (OIM) is a popular problem in social networks to learn
influence propagation model parameters and maximize the influence spread at the same …

Consider transceiver designs in a multiuser multi-input single-output (MISO) downlink
channel, where the users are to receive the same data stream simultaneously. This problem …

We study Semidefinite Programming, SDP, relaxations for Sensor Network Localization,
SNL, with anchors and with noisy distance information. The main point of the paper is to …

In this paper, we consider approximation algorithms for optimizing a generic multi-variate
homogeneous polynomial function, subject to homogeneous quadratic constraints. Such …

Many important engineering problems can be cast in the form of a quadratically constrained
quadratic program (QCQP) or a fractional QCQP. In general, these problems are nonconvex …

Finding low-rank solutions of semidefinite programs is important in many applications. For
example, semidefinite programs that arise as relaxations of polynomial optimization …

Since the early 1960s, polyhedral methods have played a central role in both the theory and
practice of combinatorial optimization. Since the early 1990s, a new technique, semidefinite …

This paper develops a new storage-optimal algorithm that provably solves almost all
semidefinite programs (SDPs). This method is particularly effective for weakly constrained …