Self-regularity J Peng, C Roos, T Terlaky
Self-Regularity, 2009
371 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
266 2002 Approximating k-means-type clustering via semidefinite programming J Peng, Y Wei
SIAM journal on optimization 18 (1), 186-205, 2007
225 2007 Equivalence of variational inequality problems to unconstrained minimization JM Peng
Mathematical Programming 78 (3), 347-355, 1997
151 1997 Scale invariant cosegmentation for image groups L Mukherjee, V Singh, J Peng
CVPR 2011, 1881-1888, 2011
141 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
122 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
97 1999 A new and efficient large-update interior-point method for linear optimization J Peng, C Roos, T Terlaky
Вычислительные технологии 6 (4), 2001
92 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
85 2004 Ensemble clustering using semidefinite programming with applications V Singh, L Mukherjee, J Peng, J Xu
Machine learning 79, 177-200, 2010
79 2010 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 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
78 2009 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
74 1999 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
64 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
61 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
58 2000 A Strongly Polynomial Rounding Procedure Yielding a Maximally Complementary Solution for T Illés, J Peng, C Roos, T Terlaky
SIAM Journal on Optimization 11 (2), 320-340, 2000
51 2000 