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Found 7 papers, 1 papers with code
Learning to Warm-Start Fixed-Point Optimization Algorithms
We introduce a machine-learning framework to warm-start fixed-point optimization algorithms.
Sums of Separable and Quadratic Polynomials
We establish that the answer to question (i) is positive for univariate plus quadratic polynomials and for convex SPQ polynomials, but negative already for bivariate quartic SPQ polynomials.
Partial Recovery in the Graph Alignment Problem
Our focus here is on partial recovery, i. e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erd\H{o}s-R\'enyi graphs of parameters $(n, q, s)$.
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics
Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics.
On the Complexity of Detecting Convexity over a Box
As a byproduct, our proof shows that the problem of testing whether all matrices in an interval family are positive semidefinite is strongly NP-hard.
Geometry of 3D Environments and Sum of Squares Polynomials
Motivated by applications in robotics and computer vision, we study problems related to spatial reasoning of a 3D environment using sublevel sets of polynomials.
DC Decomposition of Nonconvex Polynomials with Algebraic Techniques
We consider the problem of decomposing a multivariate polynomial as the difference of two convex polynomials.
