Ting Kei Pong (T. K. Pong)
I am currently an associate professor at Department of Applied Mathematics, the Hong Kong Polytechnic University.
This is my CV.
Background
I received my Bachelor degree in 2004 from the Chinese University of Hong Kong, Department of Mathematics.
I got my MPhil degree in 2006 in the same department under the supervision of Professor Kung Fu Ng.
I started my PhD study in 2006 in Department of Mathematics of University of Washington, under the supervision of Professor Paul Tseng.
After the disappearance of Professor Tseng, I was coadvised by Professor Maryam Fazel and Professor Rekha Thomas.
I was in Simon Fraser University from July 2010 to March 2011 working with Professor Zhaosong Lu as a visiting researcher.
I got my PhD degree in June 2011. From June 2011 to July 2013, I was a postdoctoral fellow at University of Waterloo, under the mentorship of Professor Stephen Vavasis
and Professor Henry Wolkowicz. From July 2013 to July 2014, I was a PIMS postdoctoral fellow at University of British Columbia,
working with Professor Michael Friedlander.
I joined the Hong Kong Polytechnic University on Aug 1st, 2014.
Teaching
I am teaching AMA4850 in semester 2, 202324.
Current Students and Postdocs:
 Hao Zhang, PhD: Chief supervisor.
 Ying Lin, PhD: Chief supervisor.
 Yuncheng Liu, postdoc.
 Ming Lei, postdoc.
 Xiaozhou Wang, postdoc.
Former Students and Postdocs:
 Peiran Yu, PhD (2021, Chief supervisor). Current affiliation: Postdoc at University of Maryland College Park.
 Lei Yang, PhD (2017, Cosupervisor). Current affiliation: Associate Professor at Sun YatSen University.
 Shuqin Sun, postdoc 20212023. Current affiliation: Lecturer at China West Normal University.
 Liaoyuan Zeng, postdoc 20202022. Current affiliation: Assistant Professor at Zhejiang University of Technology.
 Scott B. Lindstrom, postdoc 20192021. Current affiliation: Lecturer at Curtin University, Australia.
 Minglu Ye, postdoc 20172018. Current affiliation: Professor at China West Normal University.
 Tianxiang Liu, postdoc 20162018. Current affiliation: Assistant Professor at Tokyo Institute of Technology.
Research Interest
Broadly speaking: Continuous optimization
Current focus:
 Convex relaxations;
 Firstorder methods for largescale (convex or nonconvex) problems;
Other interests:
 Constraint qualifications for convex optimization.
 Statistical computation;
 Robust optimization.
Preprints

Subdifferentially polynomially bounded functions and Gaussian smoothingbased zerothorder optimization (with Ming Lei, Shuqin Sun and ManChung Yue) Submitted May 2024.

Tight error bounds for logdeterminant cones without constraint qualifications (with Ying Lin, Scott B. Lindstrom and Bruno F. Lourenço) Submitted March 2024.

KurdykaŁojasiewicz exponent via Hadamard parametrization (with Yuncheng Liu, Wenqing Ouyang and Hao Wang) Submitted February 2024.

An extended sequential quadratic method with extrapolation (with Shiqi Xu and Yongle Zhang) Submitted December 2023. Codes available at code
Publications

Optimal error bounds in the absence of constraint qualifications with applications to the pcones and beyond (with Scott B. Lindstrom and Bruno F. Lourenço) To appear in Math. Oper. Res.

FrankWolfetype methods for a class of nonconvex inequalityconstrained problems (with Guoyin Li, Xiaozhou Wang, Liaoyuan Zeng and Yongle Zhang) To appear in Math. Program. Codes available at Github page hosted by Liaoyuan Zeng.

Generalized power cones: optimal error bounds and automorphisms (with Ying Lin, Scott B. Lindstrom and Bruno F. Lourenço) SIAM J. Optim. 34, 2024, pp. 13161340.

Convergence rate analysis of a Dykstratype projection algorithm (with Xiaozhou Wang) SIAM J. Optim. 34, 2024, pp. 563589.

Doubly majorized algorithm for sparsityinducing optimization problems with regularizercompatible constraints (with Tianxiang Liu and Akiko Takeda) Comput. Optim. Appl. 86, 2023, pp. 521553. Codes available at the webpage of Tianxiang Liu.

Doubly iteratively reweighted algorithm for constrained compressed sensing models (with Shuqin Sun) Comput. Optim. Appl. 85, 2023, pp. 583619. Equation (4.5a) in the published version is messed up. Please refer to (4.5) in the ArXiv version.
code

A NewtonCG based augmented Lagrangian method for finding a secondorder stationary point of nonconvex equality constrained optimization with complexity guarantees (with Chuan He and Zhaosong Lu) SIAM J. Optim. 33, 2023, pp. 17341766.
Negative signs are unfortunately missing in Algorithm 3.1 in the published version.
Please refer to Algorithm 1 in the ArXiv version instead.

Retractionbased firstorder feasible methods for differenceofconvex programs with smooth inequality and simple geometric constraints (with Guoyin Li, Shiqi Xu and Yongle Zhang) Adv. Comput. Math. 49, 2023, Article number: 8. Codes available at code

Error bounds, facial residual functions and applications to the exponential cone (with Scott B. Lindstrom and Bruno F. Lourenço) Math. Program. 200, 2023, pp. 229278.

ρregularization subproblems: Strong duality and an eigensolverbased algorithm (with Liaoyuan Zeng) Comput. Optim. Appl. 81, 2022, pp. 337368. Codes available at Github page hosted by Liaoyuan Zeng.

KurdykaŁojasiewicz exponent via infprojection (with Guoyin Li and Peiran Yu) Found. Comput. Math. 22, 2022, pp. 11711217.

Convergence rate analysis of a sequential convex programming method with line search for a class of constrained differenceofconvex optimization problems (with Zhaosong Lu and Peiran Yu) SIAM J. Optim. 31, 2021, pp. 20242054.

Analysis and algorithms for some compressed sensing models based on L1/L2 minimization (with Peiran Yu and Liaoyuan Zeng) SIAM J. Optim. 31, 2021, pp. 15761603. code

A strictly contractive PeacemanRachford splitting method for the doubly nonnegative relaxation of the minimum cut problem (with Xinxin Li, Hao Sun and Henry Wolkowicz) Comput. Optim. Appl. 78, 2021, pp. 853891.

A hybrid penalty method for a class of optimization problems with multiple rank constraints (with Tianxiang Liu, Ivan Markovsky and Akiko Takeda) SIAM J. Matrix Anal. A. 41, 2020, pp. 12601283.

A differenceofconvex approach for split feasibility with applications to matrix factorizations and outlier detection (with Chen Chen, Lulin Tan and Liaoyuan Zeng) J. Global Optim. 78, 2020, pp. 107136. See the ArXiv version for a fix of an error in Lemma 4 and Proposition 5: changed full rank to rank r in the former, and added compactness assumption to the latter. code

A subgradientbased approach for finding the maximum feasible subsystem with respect to a set (with Minglu Ye) SIAM J. Optim. 30, 2020, pp. 12741299. code

Inner approximating the completely positive cone via the cone of scaled diagonally dominant matrices (with Mina Saee and João Gouveia) J. Global Optim. 76, 2020, pp. 383405.

Polar convolution (with Michael Friedlander and Ives Macêdo) SIAM J. Optim. 29, 2019, pp. 13661391.

Iteratively reweighted l_{1} algorithms with extrapolation (with Peiran Yu) Comput. Optim. Appl. 73, 2019, pp. 353386. code Updated on Nov 18, 2017: fixing bugs in termination criteria.

A refined convergence analysis of pDCA_{e} with applications to simultaneous sparse recovery and outlier detection (with Tianxiang Liu and Akiko Takeda) Comput. Optim. Appl. 73, 2019, pp. 69100. code

A nonmonotone alternating updating method for a class of matrix factorization problems (with Xiaojun Chen and Lei Yang) SIAM J. Optim. 28, 2018, pp. 34023430. Codes available at Lei Yang's webpage

A successive differenceofconvex approximation method for a class of nonconvex nonsmooth optimization problems (with Tianxiang Liu and Akiko Takeda) Math. Program. 176, 2019, pp. 339367. DOI:10.1007/s1010701813278. code

A proximal differenceofconvex algorithm with extrapolation (with Xiaojun Chen and Bo Wen) Comput. Optim. Appl. 69, 2018, pp. 297324. code.

Calculus of the exponent of KurdykaŁojasiewicz inequality and its applications to linear convergence of firstorder methods (with Guoyin Li)
Found. Comput. Math. 18, 2018, pp. 11991232. See also the ArXiv version for more details to the proof of Theorem 4.1; domains and ranges are added to the statement of Theorem 3.5 to remove ambiguity.

PeacemanRachford splitting for a class of nonconvex optimization problems (with Guoyin Li and Tianxiang Liu)
Comput. Optim. Appl. 68, 2017, pp. 407436. code

Twostage stochastic variational inequalities: an ERMsolution procedure (with Xiaojun Chen and Roger Wets)
Math. Program. 165, 2017, pp. 71111.

Further properties of the forwardbackward envelope with applications to differenceofconvex programming (with Tianxiang Liu)
Comput. Optim. Appl. 67, 2017, pp. 489520. code Codes further optimized and updated on June 26, 2016.

Linear convergence of proximal gradient algorithm with extrapolation for a class of nonconvex nonsmooth minimization problems (with Xiaojun Chen and Bo Wen)
SIAM J. Optim. 27, 2017, pp. 124145.

Alternating direction method of multipliers for a class of nonconvex and nonsmooth problems with applications to background/foreground extraction (with Xiaojun Chen and Lei Yang) SIAM J. Imaging Sci. 10, 2017, pp. 74110.

Penalty methods for a class of nonLipschitz optimization problems (with Xiaojun Chen and Zhaosong Lu) SIAM J. Optim. 26, 2016, pp. 14651492. code A bug in the code Lp_proj is fixed on March 6, 2017.

DouglasRachford splitting for nonconvex optimization with application to nonconvex feasibility problems (with Guoyin Li) Math. Program. 159, 2016, pp. 371401. code

Eigenvalue, quadratic programming, and semidefinite programming relaxations for a cut minimization problem (with Hao Sun, Ningchuan Wang and Henry Wolkowicz)
Comput. Optim. & Appl. 63, 2016, pp. 333364. code

Global convergence of splitting methods for nonconvex composite optimization (with Guoyin Li)
SIAM J. Optim. 25, 2015, pp. 24342460.

Gauge optimization and duality (with Michael Friedlander and Ives Macêdo) SIAM J. Optim. 24, 2014 pp. 19992022.

The generalized trust region subproblem
(with Henry Wolkowicz) Comput. Optim. & Appl. 58, 2014, pp. 273322. code Note: Section 2.2.2 requires additionally b = 0. The general case is recently considered in Section 3.1 of Taati and Salahi.

Robust least square semidefinite programming with applications
(with Guoyin Li and Alfred Ka Chun Ma) Comput. Optim. & Appl. 58, 2014, pp. 347379. code

Computing optimal experimental designs via interior point method
(with Zhaosong Lu) SIAM J. Matrix Anal. A. 34, 2013, pp. 15561580. code

Hankel matrix rank minimization with applications in system identification and realization
(with Maryam Fazel, Defeng Sun and Paul Tseng) SIAM J. Matrix Anal. A. 34, 2013, pp. 946977. code

An alternating
direction method for finding Dantzig selectors (with Zhaosong Lu and Yong
Zhang) Comput. Stat. Data An. 56, 2012, pp. 40374946. ADMDS package is available at Yong Zhang's homepage.

Edgebased
semidefinite programming relaxation of sensor network localization with lower
bound constraints Comput. Optim. & Appl. 53, 2012, pp. 2344. code

Comparing SOS and SDP relaxations of sensor network localization (with João Gouveia) Comput. Optim. & Appl. 52, 2012, pp. 609627. code

Minimizing condition number via convex programming (with Zhaosong Lu) SIAM J. Matrix
Anal. A. 32, 2011, pp. 11931211. code

(Robust)
Edgebased semidefinite programming relaxation of sensor network localization
(with Paul Tseng) Math. Program. 130, 2011, pp. 321358. code

Trace
norm regularization: reformulations, algorithms, and multitask learning
(with Paul Tseng, Shuiwang Ji and Jieping Ye) SIAM J. Optim. 20, 2010, pp.
34653489. code

Constraint
qualifications for convex inequality systems with applications in constrained
optimization (with Chong Li and K. F. Ng) SIAM J. Optim. 19, 2008, pp.
163187.

The SECQ,
linear regularity, and the strong CHIP for an infinite system of closed
convex sets in normed linear spaces (with Chong Li and K. F. Ng) SIAM J.
Optim. 18, 2007, pp. 643665.
Education Related Papers

Social resistance (with Michael Friedlander and Nathan Krislock) Comput. Sci. Eng. 18(2), 2016, pp. 98103.
Journal Editorship

Associate Editor of Mathematics of Operations Research, Jan 2019 to present.

Editorial Board Member of Computational Optimization and Applications, May 2022 to present.

Editorial Board Member of Pacific Journal of Optimization, May 2022 to present.

Associate Editor of Open Journal of Mathematical Optimization, Feb 2023 to present.
Talks

One World Optimization Seminar in Vienna (June 37, 2024), KurdykaŁojasiewicz exponent for a class of Hadamarddifferenceparameterized models.

ICIAM 2023 (Aug 2025, 2023), Convergence rate analysis of a Dykstratype projection algorithm.

Workshop on Optimization, Equilibrium and Complementarity (Aug 1619, 2023), FrankWolfe type methods for nonconvex inequalityconstrained problems.

IAM seminar (Jun 28, 2023), Error bound for conic feasibility problems: case studies on the exponential cone.

Tutte seminar (Jun 17, 2023), Error bound for conic feasibility problems: case studies on the exponential cone.

UW Distinguished Seminar in Optimization & Data (Jun 3, 2023), Error bound for conic feasibility problems: case studies on the exponential cone.

SIAM Conference of Optimization (OP23) (May 31Jun 3, 2023), FrankWolfe type methods for nonconvex inequalityconstrained problems.

PreSIAM Optimization workshop (Dima's workshop) (May 30, 2023), Convergence rate analysis of a Dykstratype projection algorithm.

International Workshop on Continuous Optimization (Dec 34, 2022), FrankWolfe type methods for nonconvex inequalityconstrained problems.

Math seminar at Nanjing University (Sep 23, 2022), Error bound for conic feasibility problems: Case studies on Exponential cone and pcones.

One World Optimization Seminar (Nov 15, 2021), Analysis and algorithms for some compressed sensing models based on the ratio of the l_{1} and l_{2} norms.

International Conference on Nonconvex and Distributed Optimization: Theory, Algorithm and Applications (May 2930, 2021), Analysis and algorithms for some compressed sensing models based on the ratio of the l_{1} and l_{2} norms.

The 64th Annual Meeting of the Australian Mathematical Society (Dec 810, 2020), Convergence rate analysis of SCP_{ls} for a class of constrained differenceofconvex optimization problems.

The 6th International Conference on Continuous Optimization (Aug 58, 2019), Gauge optimization: Duality and polar envelope.

Tutte Seminar (Jun 7, 2019), Deducing KurdykaŁojasiewicz exponent of optimization models.

Miniworkshop talk at University of Tokyo (Apr 3, 2019), Gauge optimization: Duality and polar envelope.

Seminar talk at University of Tokyo (Apr 2, 2019), Deducing KurdykaŁojasiewicz exponent of optimization models.

The Greater Bay Area workshop on Computational Optimization 2019 (Jan 2324, 2019), Deducing KurdykaŁojasiewicz exponent of optimization models.

EURO 2018 (Jul 811, 2018), Iteratively reweighted l_{1} algorithms with extrapolation.

ISMP 2018 (Jul 16, 2018), Iteratively reweighted l_{1} algorithms with extrapolation.

INFORMS International 2018 (Jun 1720, 2018), A successive differenceofconvex approximation method for a class of nonconvex nonsmooth optimization problems.

SIAM Conference on Applied Linear Algebra (May 48, 2018), A nonmonotone alternating updating method for a class of matrix factorization problems.

The workshop on Variational Analysis and Stochastic Optimization (Dec 1112, 2017), Iteratively reweighted l_{1} algorithms with extrapolation.

The 5th International Conference on Continuous Optimization (Aug 611, 2016), Explicit estimation of KL exponent and linear convergence of 1storder methods.

Trends in Optimization Seminar, UW Seattle (Jun 8, 2016), Explicit estimation of KL exponent and linear convergence of 1storder methods.

The 5th Workshop on Optimization and Risk Management (Jun 23, 2016), Explicit estimation of KL exponent and linear convergence of 1storder methods.

The 4th Workshop on Optimization and Risk Management (Dec 1617, 2015), Splitting methods for nonconvex feasibility problems.

ISMP 2015 (Jul 1217, 2015) Splitting methods for nonconvex feasibility problems.

Tutte Seminar (Jul 10, 2015) Splitting methods for nonconvex feasibility problems.

Workshop on Optimization and Data Analytics (May 1314, 2015) DouglasRachford splitting for nonconvex feasibility problems.

The 3rd Workshop on Optimization and Risk Management (Oct 2021, 2014), DouglasRachford splitting for nonconvex feasibility problems.

WCOM 2014 Spring (May 3, 2014), Gauge optimization and duality.

WCOM 2013 Autumn (Oct 5, 2013), The proximalproximal gradient algorithm, manuscript, code

Optimization Days (May 68, 2013), Generalized trust region subproblem: analysis and algorithm.

UW Optimization Seminar (Nov 20, 2012), Generalized trust region subproblem.

ISMP 2012 (Aug 1924, 2012), Generalized trust region subproblem: analysis and algorithm.

Tutte Seminar (Nov 4, 2011), Convex relaxations of sensor network localization.

Midwest Optimization Meeting 2011 (Oct 1415, 2011), Efficient solutions for largescale trust region subproblem.

Thesis defense (May 10, 2011), Convex optimization in sensor network localization and multitask learning.

SFU Optimization Seminar (Nov 4, 2010), SOS and SDP relaxations of sensor network localization.

WCOM 2010 (May 9, 2010), ESDP relaxation of sensor network localization: analysis, extensions and algorithm.

Talk at MIT (Nov 19, 2009), ESDP relaxation of sensor network localization: analysis, extensions and algorithm.

ISMP 2009 (Aug 2328, 2009), ESDP relaxation of sensor network localization: analysis, extensions and algorithm.

MOPTA 2008 (Aug 1820, 2008), ESDP relaxation of sensor network localization.

UW Optimization Seminar (Jun 3, 2008), ESDP relaxation of sensor network localization.
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