**Google Scholar**

**ResearchGate**

## Preprints

- Y.H. Zhou, C.L. Bao, C. Ding and J. Zhu, A semi-smooth Newton based augmented Lagrangian method for nonsmooth optimization on matrix manifolds, March 2021, arXiv: 2103.02855.
- Y. Cui and C. Ding, Nonsmooth composite matrix optimization: strong regularity, constraint nondegeneracy and beyond, July 2019, arXiv: 1907.13253.

## Selected publications

- Q. Zhang, X.Y. Zhao and C. Ding, Matrix optimization based Euclidean embedding with outliers, Computational Optimization and Applications, to appear, 2021, arXiv: 2012.12772.
- M.Y. Chen, K.X. Gao, X.L. Liu, Z.D. Wang, N.X. Ni, Q. Zhang, L. Chen, C. Ding, Z.H. Huang, M. Wang, S.L. Wang, F. Yu, X.Y. Zhao and D.C. Xu, THOR, Trace-Based Hardware-Driven Layer-Oriented Natural Gradient Descent Computation,
, 2021.*AAAI-21* - Z.X. Jiang, X.Y. Zhao and C. Ding, A proximal DC approach for quadratic assignment problem,
2021, arXiv:1908.04522.**Computational Optimization and Applications,** - C. Ding, D.F. Sun, J. Sun and K.C. Toh, Spectral operators of matrices: semismoothness and characterizations of the generalized Jacobian,
, 30, 630–659 (2020), arXiv: 1810.09856. Revised from the second part of arXiv: 1401.2269, January 2014.*SIAM Journal on Optimization* - C. Ding, D.F. Sun, J. Sun and K.C. Toh, Spectral operator of matrices,
, 168, 509–531 (2018). Revised from the first part of arXiv: 1401.2269, January 2014.**Mathematical Programming** - Y. Cui, C. Ding and X.Y. Zhao, Quadratic growth conditions for convex matrix optimization problems associated with spectral functions,
, 27, 2332–2355 (2017).**SIAM Journal on Optimization** - C. Ding, D.F. Sun and L.W. Zhang, Characterization of the robust isolated calmness for a class of conic programming problems,
, 27, 67–90 (2017).**SIAM Journal on Optimization** - C. Ding and H.D. Qi, Convex optimization learning of faithful Euclidean distance representations in nonlinear dimensionality reduction,
, 164, 341–381 (2017).**Mathematical Programming** - C. Ding, Variational analysis of the Ky Fan k-norm,
, 25, 265–296 (2017).**Set-Valued and Variational Analysis** - C. Ding and H.D. Qi, Convex euclidean distance embedding for collaborative position localization with NLOS mitigation,
, 66, 187–218 (2017).**Computational Optimization and Applications** - C. Ding and H.D. Qi, A computable characterization of the extrinsic mean of reflection shapes and its asymptotic properties,
, 32, 1540005 (2015).**Asia-Pacific Journal of Operational Research** - B. Wu, C. Ding, D.F. Sun and K.C. Toh, On the Moreau-Yosida regularization of the vector k-norm related functions,
, 24, 766–794 (2014).**SIAM Journal on Optimization** - C. Ding, D.F. Sun and J.J. Ye, First order optimality conditions for mathematical programs with semidefinite cone complementarity constraints,
,147, 539–579 (2014).**Mathematical Programming** - C. Ding, D.F. Sun and K.C. Toh, An introduction to a class of matrix cone programming,
**Mathematical Programming**144, 141–179 (2014).**,**

## Selected Talks

- Perturbation analysis of matrix optimization, ICCOPT2019, Berlin, Germany.
- Matrix optimization: recent progress on algorithm foundation, ISMP2018, Bordeaux, France.
- Characterization of the Robust Isolated Calmness for a Class of Conic Programming Problems, SIAM OP17, Vancouver, Canada.
- Convex Optimization Learning of Faithful Euclidean Distance Representations in Nonlinear Dimensionality Reduction, ICCOPT 2016, Tokyo, Japan.
- First Order Optimality Conditions for Mathematical Programs with SDP Cone Complementarity Constraints, ISMP2012, Berlin, Germany.
- An Introduction to a Class of Matrix Cone Programming, SIAM OP11, Darmstadt, Germany.