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We study to what extent quantum algorithms can speed up solving convex optimization problems.
On computing the minima of quadratic forms (preliminary report)
Andrew Chi-Chih Yao · 1975
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Geometric Algorithms and Combinatorial Optimization
Martin Grötschel, László Lovász, and Alexander Schrijver · 1988
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A quantum algorithm for finding the minimum
Christoph Dürr and Peter Høyer · 1996
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A fast quantum mechanical algorithm for database search
Lov K. Grover · 1996
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Strengths and weaknesses of quantum computing
Charles H. Bennett, Ethan Bernstein, Gilles Brassard, and Umesh Vazirani · 1997
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A better lower bound for quantum algorithms searching an ordered list
Andris Ambainis · 1999
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Quantum computation and quantum information
Michael A. Nielsen and Isaac L. Chuang · 2000
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Quantum speed-up of Markov chain based algorithms
Márió Szegedy · 2004
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Fast quantum algorithm for numerical gradient estimation
Stephen P. Jordan · 2005
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Quantum algorithms for matching and network flows
Andris Ambainis and Robert Špalek · 2006
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Quantum query complexity of some graph problems
Christoph Dürr, Mark Heiligman, Peter Høyer, and Mehdi Mhalla · 2006
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Negative weights make adversaries stronger
Peter Høyer, Troy Lee, and Robert Špalek · 2007
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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation
Andreas Griewank and Andrea Walther · 2008
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Quantum Computation Beyond the Circuit Model
Stephen P. Jordan · 2008
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Quantum speed-ups for solving semidefinite programs
Fernando G. S. L. Brandão and Krysta M. Svore · 2017
Later among the works it cites.
Efficient algorithms for tensor scaling, quantum marginals, and moment polytopes
Peter Bürgisser, Cole Franks, Ankit Garg, Rafael Oliveira, Michael Walter, and Avi Wigderson · 2018
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Quantum algorithms and lower bounds for convex optimization
Shouvanik Chakrabarti, Andrew M. Childs, Tongyang Li, and Xiaodi Wu · 2018
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A quantum interior point method for LPs and SDPs
Iordanis Kerenidis and Anupam Prakash · 2018
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Sébastien Bubeck · 2015
Cited alongside, same era.
A faster cutting plane method and its implications for combinatorial and convex optimization
Yin Tat Lee, Aaron Sidford, and Sam Chiu-wai Wong · 2015
Cited alongside, same era.
Quantum SDP-solvers: Better upper and lower bounds
Joran van Apeldoorn, András Gilyén, Sander Gribling, and Ronald de Wolf · 2017
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Yin Tat Lee, Aaron Sidford, and Santosh S. Vempala · 2018
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Improvements in quantum SDP-solving with applications
Joran van Apeldoorn and András Gilyén · 2019
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Quantum SDP solvers: Large speed-ups, optimality, and applications to quantum learning
Fernando G. S. L. Brandão, Amir Kalev, Tongyang Li, Cedric Yen-Yu Lin, Krysta M. Svore, and Xiaodi Wu · 2019
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Optimizing quantum optimization algorithms via faster quantum gradient computation
András Gilyén, Srinivasan Arunachalam, and Nathan Wiebe · 2019
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