J
Jaehyun Park
Researcher at Stanford University
Publications - 4
Citations - 214
Jaehyun Park is an academic researcher from Stanford University. The author has contributed to research in topics: Semidefinite programming & Relaxation (approximation). The author has an hindex of 4, co-authored 4 publications receiving 171 citations.
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General Heuristics for Nonconvex Quadratically Constrained Quadratic Programming
Jaehyun Park,Stephen Boyd +1 more
TL;DR: The Suggest-and-Improve framework for general nonconvex quadratically constrained quadratic programs (QCQPs) is introduced and an open-source Python package QCQP is introduced, which implements the heuristics discussed in the paper.
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A semidefinite programming method for integer convex quadratic minimization
Jaehyun Park,Stephen Boyd +1 more
TL;DR: By interpreting the solution to the SDP relaxation probabilistically, a randomized algorithm for finding good suboptimal solutions is obtained, and thus an upper bound on the optimal value of the problem.
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A Semidefinite Programming Method for Integer Convex Quadratic Minimization
Jaehyun Park,Stephen Boyd +1 more
TL;DR: In this article, a simple semidefinite programming (SDP) relaxation was proposed to obtain a nontrivial lower bound on the optimal value of the problem of minimizing a convex quadratic function over the integer lattice.
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Concave Quadratic Cuts for Mixed-Integer Quadratic Problems
Jaehyun Park,Stephen Boyd +1 more
TL;DR: In this article, concave quadratic inequalities that hold for any vector in the integer lattice Z n, and show that adding these inequalities to a mixed-integer nonconvex QCQP can improve the SDP-based bound on the optimal value.