# Jiming Peng

According to our database

Collaborative distances:

^{1}, Jiming Peng authored at least 45 papers between 2000 and 2020.Collaborative distances:

## Timeline

#### Legend:

Book In proceedings Article PhD thesis Other## Links

#### On csauthors.net:

## Bibliography

2020

J. Glob. Optim., 2020

2019

New global algorithms for quadratic programming with a few negative eigenvalues based on alternative direction method and convex relaxation.

Math. Program. Comput., 2019

Manag. Sci., 2019

Enhancing Semidefinite Relaxation for Quadratically Constrained Quadratic Programming via Penalty Methods.

J. Optim. Theory Appl., 2019

2018

J. Glob. Optim., 2018

Comput. Optim. Appl., 2018

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

J. Glob. Optim., 2017

2016

Proceedings of the Computer Vision - ECCV 2016, 2016

2015

A nonlinear semidefinite optimization relaxation for the worst-case linear optimization under uncertainties.

Math. Program., 2015

New Analysis on Sparse Solutions to Random Standard Quadratic Optimization Problems and Extensions.

Math. Oper. Res., 2015

Eur. J. Oper. Res., 2015

Semi-definite programming relaxation of quadratic assignment problems based on nonredundant matrix splitting.

Comput. Optim. Appl., 2015

2014

Analytical Results and Efficient Algorithm for Optimal Portfolio Deleveraging with Market Impact.

Oper. Res., 2014

2013

Math. Program., 2013

2012

J. Glob. Optim., 2012

Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging.

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Estimating Bounds for Quadratic Assignment Problems Associated with Hamming and Manhattan Distance Matrices Based on Semidefinite Programming.

SIAM J. Optim., 2010

A new relaxation framework for quadratic assignment problems based on matrix splitting.

Math. Program. Comput., 2010

Mach. Learn., 2010

Learning kernels for variants of normalized cuts: Convex relaxations and applications.

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009

Optimization-Based Dynamic Sensor Management for Distributed Multitarget Tracking.

IEEE Trans. Syst. Man Cybern. Part C, 2009

J. Comb. Optim., 2009

Comput. Manag. Sci., 2009

A confidence voting process for ranking problems based on support vector machines.

Ann. Oper. Res., 2009

2008

PREFACESpecial section on mathematical programming in data mining and machine learning.

Optim. Methods Softw., 2008

2007

SIAM J. Optim., 2007

SIAM J. Optim., 2007

Exact Penalty Functions for Constrained Minimization Problems via Regularized Gap Function for Variational Inequalities.

J. Glob. Optim., 2007

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

2006

Proceedings of the International Joint Conference on Neural Networks, 2006

2005

A Predictor-Corrector Algorithm for Linear Optimization Based on a Specific Self-Regular Proximity Function.

SIAM J. Optim., 2005

Proceedings of the 2005 SIAM International Conference on Data Mining, 2005

Proceedings of the Computational Science and Its Applications, 2005

Proceedings of the Computing and Combinatorics, 11th Annual International Conference, 2005

2002

Primal-Dual Interior-Point Methods for Second-Order Conic Optimization Based on Self-Regular Proximities.

SIAM J. Optim., 2002

Optim. Methods Softw., 2002

Self-regular functions and new search directions for linear and semidefinite optimization.

Math. Program., 2002

A new class of polynomial primal-dual methods for linear and semidefinite optimization.

Eur. J. Oper. Res., 2002

Self-regularity - a new paradigm for primal-dual interior-point algorithms.

Princeton series in applied mathematics, Princeton University Press, ISBN: 978-0-691-09193-8, 2002

2001

A Scaled Gauss--Newton Primal-Dual Search Direction for Semidefinite Optimization.

SIAM J. Optim., 2001

2000

A Strongly Polynomial Rounding Procedure Yielding a Maximally Complementary Solution for P<sub>*(kappa)</sub> Linear Complementarity Problems.

SIAM J. Optim., 2000

New Complexity Analysis of the Primal - Dual Newton Method for Linear Optimization.

Ann. Oper. Res., 2000