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 AMA542 in semester 2, 202021.
Current Students and Postdocs:
Former Students and Postdocs:
 Lei Yang, PhD (2017, Cosupervisor). Current affiliation: Postdoc at NUS.
 Scott B. Lindstrom, postdoc 20192021. Current affiliation: Postdoc at Curtin University, Australia.
 Tianxiang Liu, postdoc 20162018. Current affiliation: Assistant Professor at Tokyo Institute of Technology.
 Minglu Ye, postdoc 20172018. Current affiliation: Professor at China West Normal University.
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

Retractionbased firstorder feasible methods for differenceofconvex programs with smooth inequality and simple geometric constraints (with Guoyin Li and Yongle Zhang) Submitted June 2021. code

Error bounds, facial residual functions and applications to the exponential cone (with Scott B. Lindstrom and Bruno F. Lourenço) Submitted December 2020.
Publications

KurdykaLojasiewicz exponent via infprojection (with Guoyin Li and Peiran Yu) To appear in Found. Comput. Math. DOI: https://doi.org/10.1007/s10208021095286.

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) To appear in SIAM J. Optim.

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. 853–891.

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 Joao Gouveia) J. Global Optim. 76, 2020, pp. 383405.

Polar convolution (with Michael Friedlander and Ives Macedo) 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 KurdykaLojasiewicz 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.

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 Macedo) 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 Joao 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.
Talks

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 (June 7, 2019), Deducing KurdykaLojasiewicz exponent of optimization models.

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

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

The Greater Bay Area workshop on Computational Optimization 2019 (January 23  24, 2019), Deducing KurdykaLojasiewicz exponent of optimization models.

EURO 2018 (July 8  11, 2018), Iteratively reweighted l_{1} algorithms with extrapolation.

ISMP 2018 (July 1  6, 2018), Iteratively reweighted l_{1} algorithms with extrapolation.

INFORMS International 2018 (Jun 17  20, 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 (June 8, 2016), Explicit estimation of KL exponent and linear convergence of 1storder methods.

The 5th Workshop on Optimization and Risk Management (June 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 (July 1217, 2015) Splitting methods for nonconvex feasibility problems.

Tutte Seminar (July 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 (June 3, 2008), ESDP relaxation of sensor network localization.
Links
Last modified on