Self-regularity: a new paradigm for primal-dual interior-point algorithms J Peng, C Roos, T Terlaky Princeton University Press, 2009 | 386 | 2009 |

Self-regular functions and new search directions for linear and semidefinite optimization J Peng, C Roos, T Terlaky Mathematical Programming 93 (1), 129-171, 2002 | 274 | 2002 |

Approximating k-means-type clustering via semidefinite programming J Peng, Y Wei SIAM journal on optimization 18 (1), 186-205, 2007 | 242 | 2007 |

Equivalence of variational inequality problems to unconstrained minimization JM Peng Mathematical Programming 78 (3), 347-355, 1997 | 152 | 1997 |

Scale invariant cosegmentation for image groups L Mukherjee, V Singh, J Peng CVPR 2011, 1881-1888, 2011 | 143 | 2011 |

Optimal nearly analytic discrete approximation to the scalar wave equation D Yang, J Peng, M Lu, T Terlaky Bulletin of the Seismological Society of America 96 (3), 1114-1130, 2006 | 126 | 2006 |

Optimality conditions for the minimization of a quadratic with two quadratic constraints JM Peng, YX Yuan SIAM Journal on Optimization 7 (3), 579-594, 1997 | 126 | 1997 |

On Mehrotra-type predictor-corrector algorithms M Salahi, J Peng, T Terlaky SIAM Journal on Optimization 18 (4), 1377-1397, 2008 | 104 | 2008 |

A non-interior continuation method for generalized linear complementarity problems JM Peng, Z Lin Mathematical Programming 86, 533-563, 1999 | 104 | 1999 |

A new and efficient large-update interior-point method for linear optimization J Peng, C Roos, T Terlaky Вычислительные технологии 6 (4), 2001 | 94 | 2001 |

An optimal nearly analytic discrete method for 2D acoustic and elastic wave equations D Yang, M Lu, R Wu, J Peng Bulletin of the Seismological Society of America 94 (5), 1982-1992, 2004 | 86 | 2004 |

A hybrid Newton method for solving the variational inequality problem via the D-gap function JM Peng, M Fukushima Mathematical Programming 86, 367-386, 1999 | 80 | 1999 |

Ensemble clustering using semidefinite programming with applications V Singh, L Mukherjee, J Peng, J Xu Machine learning 79, 177-200, 2010 | 79 | 2010 |

Optimization-based dynamic sensor management for distributed multitarget tracking R Tharmarasa, T Kirubarajan, J Peng, T Lang IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2009 | 79 | 2009 |

Primal-dual interior-point methods for second-order conic optimization based on self-regular proximities J Peng, C Roos, T Terlaky SIAM Journal on Optimization 13 (1), 179-203, 2002 | 79 | 2002 |

A new class of polynomial primal–dual methods for linear and semidefinite optimization J Peng, C Roos, T Terlaky European Journal of Operational Research 143 (2), 234-256, 2002 | 72 | 2002 |

A new theoretical framework for k-means-type clustering J Peng, Y Xia Foundations and advances in data mining, 79-96, 2005 | 67 | 2005 |

A simply constrained optimization reformulation of KKT systems arising from variational inequalities F Facchinei, A Fischer, C Kanzow, J -M. Peng Applied Mathematics and Optimization 40, 19-37, 1999 | 62 | 1999 |

New complexity analysis of the primal—Dual Newton method for linear optimization J Peng, C Roos, T Terlaky Annals of operations research 99, 23-39, 2000 | 59 | 2000 |

A Strongly Polynomial Rounding Procedure Yielding a Maximally Complementary Solution for Linear Complementarity Problems T Illés, J Peng, C Roos, T Terlaky SIAM Journal on Optimization 11 (2), 320-340, 2000 | 53 | 2000 |