Dr. Zheng Qu

Dr. Zheng Qu

Posts by Collection

portfolio

publications

Curse of dimensionality reduction in max-plus based approximation methods: theoretical estimates and improved pruning algorithms

Stephane Gaubert, William M.

Published in IEEE 50th Conference on Decision and Control and European Control Conference (CDC), pp.1054-1061, Orlando, 2011

Cite as: Stephane Gaubert, William M. McEneaney and Zheng Qu. (2011). "Curse of dimensionality reduction in max-plus based approximation methods: theoretical estimates and improved pruning algorithms." IEEE 50th Conference on Decision and Control and European Control Conference (CDC), pp.1054-1061, Orlando.
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Markov operators on cones and non-commutative consensus

Stephane Gaubert, Zheng Qu.

Published in Proceedings of the 12th biannual European Control Conference (ECC), pp.2693-2700, 2013

Cite as: Stephane Gaubert, Zheng Qu. (2013). "Markov operators on cones and non-commutative consensus." Proceedings of the 12th biannual European Control Conference (ECC), pp.2693-2700.

Contraction of Riccati flows applied to the convergence analysis of the max-plus curse of dimensionality free method

Zheng Qu.

Published in Proceedings of the 12th biannual European Control Conference (ECC), pp.2226-2231, 2013

Cite as: Zheng Qu. (2013). "Contraction of Riccati flows applied to the convergence analysis of the max-plus curse of dimensionality free method." Proceedings of the 12th biannual European Control Conference (ECC), pp.2226-2231.

Dobrushin ergodicity coefficient for Markov operators on cones

Stephane Gaubert, Zheng Qu.

Published in Integral Equations and Operator Theory, 81(1):127-150, 2014

Cite as: Stephane Gaubert, Zheng Qu. (2014). "Dobrushin ergodicity coefficient for Markov operators on cones." Integral Equations and Operator Theory, 81(1):127-150.
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The contraction rate in Thompson metric of order-preserving flows on a cone - application to generalized Riccati equations

Stephane Gaubert, Zheng Qu.

Published in Journal of Differential Equations, 256(8):2902-2948, 2014

Cite as: Stephane Gaubert, Zheng Qu. (2014). "The contraction rate in Thompson metric of order-preserving flows on a cone - application to generalized Riccati equations." Journal of Differential Equations, 256(8):2902-2948.
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Contraction of Riccati flows applied to the convergence analysis of a max-plus curse of dimensionality free method

Zheng Qu.

Published in SIAM Journal on Control and Optimization, 52(5):2677-2706, 2014

Cite as: Zheng Qu. (2014). "Contraction of Riccati flows applied to the convergence analysis of a max-plus curse of dimensionality free method." SIAM Journal on Control and Optimization, 52(5):2677-2706.
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Bundle-based pruning in the max-plus curse of dimensionality free method

Stephane Gaubert, Zheng Qu and Srinivas Sridharan.

Published in Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS), Groningen, 2014

Cite as: Stephane Gaubert, Zheng Qu and Srinivas Sridharan. (2014). "Bundle-based pruning in the max-plus curse of dimensionality free method." Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS), Groningen.

A max-plus based randomized algorithm for solving a class of HJB PDEs

Zheng Qu.

Published in 53rd IEEE Conference on Decision and Control (CDC), Los Angeles, CA, pp. 1575-1580, 2014

Cite as: Zheng Qu. (2014). "A max-plus based randomized algorithm for solving a class of HJB PDEs." 53rd IEEE Conference on Decision and Control (CDC), Los Angeles, CA, pp. 1575-1580.
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Stochastic Dual Coordinate Ascent with Adaptive Probabilities

Dominik Csiba, Zheng Qu and Peter Richtárik.

Published in Proceedings of the 32nd International Conference on Machine Learning (ICML), PMLR 37:674-683, 2015

Cite as: Dominik Csiba, Zheng Qu and Peter Richtárik. (2015). "Stochastic Dual Coordinate Ascent with Adaptive Probabilities." Proceedings of the 32nd International Conference on Machine Learning (ICML), PMLR 37:674-683.
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Randomized dual coordinate ascent with arbitrary sampling

Zheng Qu, Peter Richtárik and Tong Zhang.

Published in Advances in Neural Information Processing Systems (NeurIPS) 28, pp. 865-873, 2015

Cite as: Zheng Qu, Peter Richtárik and Tong Zhang. (2015). "Randomized dual coordinate ascent with arbitrary sampling." Advances in Neural Information Processing Systems (NeurIPS) 28, pp. 865-873.
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Maximizing concave piecewise affine functions on the unitary group

Stephane Gaubert, Zheng Qu and Srinivas Sridharan.

Published in Optimization Letters, 10(4):655-665, 2016

Cite as: Stephane Gaubert, Zheng Qu and Srinivas Sridharan. (2016). "Maximizing concave piecewise affine functions on the unitary group." Optimization Letters, 10(4):655-665.
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Coordinate descent with arbitrary sampling I: algorithms and complexity

Zheng Qu, Peter Richtárik.

Published in Optimization Methods and Software, 31(5):829-857, 2016

Cite as: Zheng Qu, Peter Richtárik. (2016). "Coordinate descent with arbitrary sampling I: algorithms and complexity." Optimization Methods and Software, 31(5):829-857.
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Coordinate descent with arbitrary sampling II: expected separable overapproximation

Zheng Qu, Peter Richtárik.

Published in Optimization Methods and Software,31(5):858-884, 2016

Cite as: Zheng Qu, Peter Richtárik. (2016). "Coordinate descent with arbitrary sampling II: expected separable overapproximation." Optimization Methods and Software,31(5):858-884.
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Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling

Zeyuan Allen-Zhu, Zheng Qu, Peter Richtárik and Yang Yuan.

Published in Proceedings of the 33rd International Conference on Machine Learning (ICML), PMLR 48:1110-1119, 2016

Cite as: Zeyuan Allen-Zhu, Zheng Qu, Peter Richtárik and Yang Yuan. (2016). "Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling." Proceedings of the 33rd International Conference on Machine Learning (ICML), PMLR 48:1110-1119.
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SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization

Zheng Qu, Peter Richtárik, Martin Takáč and Olivier Fercoq.

Published in Proceedings of the 33rd International Conference on Machine Learning (ICML), PMLR 48:1823-1832, 2016

Cite as: Zheng Qu, Peter Richtárik, Martin Takáč and Olivier Fercoq. (2016). "SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization." Proceedings of the 33rd International Conference on Machine Learning (ICML), PMLR 48:1823-1832.
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Checking the strict positivity of Kraus maps is NP-hard

Stephane Gaubert, Zheng Qu.

Published in Information Processing Letters, 118:35-43, 2017

Cite as: Stephane Gaubert, Zheng Qu. (2017). "Checking the strict positivity of Kraus maps is NP-hard." Information Processing Letters, 118:35-43.
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S2CD: Semi-stochastic coordinate descent

Jakub Konečný, Zheng Qu and Peter Richtárik.

Published in Optimization Methods and Software, 32:993-1005, 2017

Cite as: Jakub Konečný, Zheng Qu and Peter Richtárik. (2017). "S2CD: Semi-stochastic coordinate descent." Optimization Methods and Software, 32:993-1005.
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Polyhedron overapproximation for complexity reduction in static analysis

Yassamine Seladji, Zheng Qu.

Published in International Journal of Computer Mathematics: Computer Systems Theory, 2018

Cite as: Yassamine Seladji, Zheng Qu. (2018). "Polyhedron overapproximation for complexity reduction in static analysis." International Journal of Computer Mathematics: Computer Systems Theory.
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Adaptive restart of accelerated gradient methods under local quadratic growth condition

Olivier Fercoq, Zheng Qu.

Published in IMA Journal of Numerical Analysis, 39(4):2069-2095, 2019

Cite as: Olivier Fercoq, Zheng Qu. (2019). "Adaptive restart of accelerated gradient methods under local quadratic growth condition." IMA Journal of Numerical Analysis, 39(4):2069-2095.
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SAGA with arbitrary sampling

Xun Qian, Zheng Qu and Peter Richtárik.

Published in Proceedings of the 36th International Conference on Machine Learning (ICML), PMLR 97:5190-5199, 2019

Cite as: Xun Qian, Zheng Qu and Peter Richtárik. (2019). "SAGA with arbitrary sampling." Proceedings of the 36th International Conference on Machine Learning (ICML), PMLR 97:5190-5199.
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Solving ergodic Markov decision processes and perfect information Zero-sum stochastic games by variance reduced deflated value iteration

Marianne Akian, Stephane Gaubert, Zheng Qu and Omar Saadi.

Published in IEEE 58th Conference on Decision and Control (CDC), Nice, France, pp. 5963-5970, 2019

Cite as: Marianne Akian, Stephane Gaubert, Zheng Qu and Omar Saadi. (2019). "Solving ergodic Markov decision processes and perfect information Zero-sum stochastic games by variance reduced deflated value iteration." IEEE 58th Conference on Decision and Control (CDC), Nice, France, pp. 5963-5970.
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Restarting the accelerated coordinate descent method with a rough strong convexity estimate

Olivier Fercoq, Zheng Qu.

Published in Computational Optimization and Applications, 75:63-91, 2020

Cite as: Olivier Fercoq, Zheng Qu. (2020). "Restarting the accelerated coordinate descent method with a rough strong convexity estimate." Computational Optimization and Applications, 75:63-91.
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L-SVRG and L-Katyusha with arbitrary sampling

Xun Qian, Zheng Qu and Peter Richtárik.

Published in Journal of Machine Learning Research, 22(112), 1-47, 2021

Cite as: Xun Qian, Zheng Qu and Peter Richtárik. (2021). "L-SVRG and L-Katyusha with arbitrary sampling." Journal of Machine Learning Research, 22(112), 1-47.
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An inexact proximal augmented Lagrangian framework with arbitrary linearly convergent inner solver for composite convex optimization

Fei Li, Zheng Qu.

Published in Mathematical Programming Computation 13, 583-644, 2021

Cite as: Fei Li, Zheng Qu. (2021). "An inexact proximal augmented Lagrangian framework with arbitrary linearly convergent inner solver for composite convex optimization." Mathematical Programming Computation 13, 583-644.
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Multiply accelerated value iteration for non-symmetric affine fixed point problems and application to Markov decision processes

Marianne Akian, Stephane Gaubert, Zheng Qu and Omar Saadi.

Published in SIAM Journal on Matrix Analysis and Applications 43(1), 199-232, 2022

Cite as: Marianne Akian, Stephane Gaubert, Zheng Qu and Omar Saadi. (2022). "Multiply accelerated value iteration for non-symmetric affine fixed point problems and application to Markov decision processes." SIAM Journal on Matrix Analysis and Applications 43(1), 199-232.
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A correlatively sparse Lagrange multiplier expression relaxation for polynomial optimization

Zheng Qu and Xindong Tang.

Published in SIAM Journal on Optimization 34(1), 127-162, 2024

Cite as: Zheng Qu and Xindong Tang. (2024). "A correlatively sparse Lagrange multiplier expression relaxation for polynomial optimization." SIAM Journal on Optimization 34(1), 127-162.
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Exactness and effective degree bound of Lasserre’s relaxation for polynomial optimization over finite variety

Zheng Hua and Zheng Qu.

Published in Mathematics of Operations Research, 2025

Cite as: Zheng Hua and Zheng Qu. (2025). "Exactness and effective degree bound of Lasserre's relaxation for polynomial optimization over finite variety." Mathematics of Operations Research.
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A characterization for tightness of the sparse Moment-SOS hierarchy

Jiawang Nie, Zheng Qu, Xindong Tang and Linghao Zhang.

Published in Mathematical Programming, 2025

Cite as: Jiawang Nie, Zheng Qu, Xindong Tang and Linghao Zhang. (2025). "A characterization for tightness of the sparse Moment-SOS hierarchy." Mathematical Programming.
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Globally solving concave quadratic programs via doubly nonnegative relaxation

Zheng Qu, Tianyou Zeng and Yuchen Lou.

Published in Mathematical Programming Computation, 2025

Cite as: Zheng Qu, Tianyou Zeng and Yuchen Lou. (2025). "Globally solving concave quadratic programs via doubly nonnegative relaxation." Mathematical Programming Computation 17, 451–503.
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talks

teaching

Operations Research (MATH3901)

Undergraduate course, Department of Mathematics, University of Hong Kong, 2015

Regular undergraduate teaching conducted each spring semester from 2015 through 2024. This course covers fundamental theory and algorithms of linear programming.

Probability Theory (MATH3603)

Undergraduate course, Department of Mathematics, University of Hong Kong, 2015

Regular undergraduate teaching conducted each fall semester from 2015 through 2024. This course provides an introduction to probability theory and its applications.

Numerical Analysis (Fall 2025)

Undergraduate course, School of mathematical sciences, Shenzhen University, 2025

This course covers fundamental topics in numerical analysis, including numerical solutions to equations, interpolation, numerical differentiation and integration, and numerical solutions to differential equations.