PUBLICATIONS OF Yu-Hong DAI

  1. Z.W. Chen, Y.H. Dai and J. Liu, On the Superlinear Local Convergence of a Penalty-Free Method, Submitted to Mathematical Programming.
  2. Z.W. Chen, Y.H. Dai and F. Liu, A Penalty-Free Line Search Method for Inequality Constrained Optimization with Infeasibility Detection, Submitted to IMA Journal of Numerical Analysis.
  3. F.M. Xu, Y.H. Dai, Z.H. Zhao and Z.B. Xu, Efficient Projected Gradient Methods for A Class of $L_0$ Constrained Optimization Problems, Submitted to Mathematical Programming.
  4. R. Diao, Y.F. Liu and Y.H. Dai, A New Fully Polynomial Time Approximation Scheme for the Interval Subset Sum Problem, Submitted to Journal of Global Optimization, in revision.
  5. Y.H. Dai, D. Han, X. Yuan and W. Zhang,A Squential Updating Scheme of the Lagrangian Multiplier for Separable Convex Programming, Mathematics of Computation, Vol. 86, No. 303, pp. 315-343, 2016.
  6. Y.F. Liu, S. Ma, Y.H. Dai and S. Zhang,A Smoothing SQP Framework for A Class of Composite $L_q$ Minimization over Polyhedron, Mathematical Programming, Ser. A, Vol. 158, pp. 467-500, 2016.
  7. Y. Chen, Y.H. Dai and D. Han, Fiber Orientation Distribution Estimation Using A Peaceman-Rachford Splitting Method, SIAM Journal on Imaging Sciences, Vol. 9, No. 2, pp. 573-604, 2016.
  8. Y.H. Dai and C.X. Kou, A Barzilai-Borwein Conjugate Gradient Method, Science China Mathematics, Vol. 59, No. 8, pp. 1511-1524, 2016.
  9. C. Tan, S. Ma, Y.H. Dai and Y. Qian, Barzilai-Borwein Step Size for Stochastic Gradient Descent, The 30th Conference on Neural Information Processing Systems (NIPS), Barcelona, Spain, 2016 (accepted)
  10. Z.W. Chen and Y.H. Dai, A Line Search Exact Penalty Method with Bi-Object Strategy for Nonlinear Constrained Optimization, Journal of Computational and Applied Mathematics, Vol. 300, pp. 245-258, 2016.
  11. F. Xu, M. Sun and Y.H. Dai, An Adaptive Lagrangian Algorithm for Optimal Portofolio Deleveraging with Cross-Impact, Journal of Systems Science and Complexity, 2016 (to appear)
  12. Z.B. Li and Y.H. Dai, Optimal Beamformer Design in the Reverberant Environment (in Chinese), Scientia Sinica Mathematica, Vol. 46, No. 6, pp. 877-892, 2016.
  13. M. Liu, C. Cui, X. Tong and Y.H. Dai,Algorithms, Softwares and Recent developments of Mixed Integer Nonlinear Programming (in Chinese), Scientia Sinica Mathematica, Vol. 46, No. 1, pp. 1-20, 2016.
  14. M. Liu, X. Tong and Y.H. Dai, Algorithms and Recent Developments of Packing Problems, Mathematica Numerica Sinica, Vol. 38, No. 3, pp. 257-280, 2016.
  15. G.X. Li, W.K. Chen, Z. Wan and Y.H. Dai, Integer Programming Model for Transport Aircraft Fleet Cargo Loading, Journal on Numerical Methods and Computer Applications, Vol. 37, No. 3, pp. 233-244, 2016.
  16. Y.H. Dai, M. Al-Baali and X. Yang, A Positive Barzilai-Borwein-Like Stepsize and An Extension for Symmetric Linear Systems, In: M. Al-Baali, L. Grandinetti and A. Purnama eds., Vol. 134 of the series Springer Proceedings in Mathematics & Statistics: Numerical Analysis and Optimization, pp. 59-75, 2015.
  17. B. Jiang and Y.H. Dai, A Framework of Constraint Preserving Update Schemes for Optimization on Stiefel Manifold, Mathematical Programming, Ser. A, Vol. 153, No. 2, pp. 535-575, 2015.
  18. Y.F. Liu, Y.H. Dai and S. Ma, Joint Power and Admission Control: Non-Convex Approximation and An Effective Polynomial Time Deflation Approach, IEEE Transactions on Signal Processing, Vol. 63, No. 14, pp. 3641-3656, 2015.
  19. C.X. Kou and Y.H. Dai, A Modified Self-Scaling Memoryless Broyden-Fletcher-Goldfarb- Shanno Method for Unconstrained Optimization, Journal of Optimization Theory and Applications, Vol. 165, pp. 209-224, 2015.
  20. C. Hao, C. Cui and Y.H. Dai, A Sequential Subspace Projection Method for Extreme Z-Eigenvalues of Supersymmetric Tensors, Numerical Linear Algebra and Applications, Vol. 22, pp. 283-298, 2015.
  21. H. Gao, Y.H. Dai and X.J. Tong, Barzilai-Borwein-Like Methods for The Extreme Eigenvalue Problem, Journal of Industrial and Management Optimization, Vol. 11, No. 3, pp. 999-1019, 2015.
  22. C. Hao, C. Cui and Y.H. Dai, A Feasible Trust-Region Method for Calculating Extreme Z-Eigenvalues of Symmetric Tensors, Pacific Journal of Optimization, , Vol. 11, No. 2, pp. 291-307, 2015.
  23. Y.H. Dai and N. Yamashita, Analysis of Sparse Quasi-Newton Updates with Positive Definite Matrix Completion, Journal of the Operations Research Society of China, Vol. 2, No. 1, pp. 39-56, 2014.
  24. Y.F. Liu and Y.H. Dai, On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA Systems, IEEE Transactions on Signal Processing, Vol. 62, No. 3, pp. 583-596, 2014.
  25. C. Cui, Y.H. Dai and J.W. Nie, All Real Eigenvalues of Symmetric Tensors, SIAM Journal on Matrix Analysis and Applications, Vol. 35, No. 4, pp. 1582-1601, 2014.
  26. B. Jiang, C. Cui and Y.H. Dai, Unconstrained Optimization Models for Computing Several Extreme Eigenpairs of Real Symmetric Matrices, Pacific Journal of Optimization, 10:1, pp. 55-71, 2014.
  27. Y.Q. Hu, C. Hao and Y.H. Dai, Projected Gradient Algorithms for Optimization over Order Simplices, Optimization Methods and Software, Vol. 29, No. 5, 1090-1117, 2014.
  28. Y.H.Dai and X.W. Liu, Advances in linear and nonlinear programming (in Chinese), Operations Research Transactions, Vol. 18, No. 1, pp. 69-92, 2014.
  29. Y.H. Dai, A Perfect Example for the BFGS Method, Mathematical Programming, Vol. 138, No. 1-2, pp. 501-530, 2013.
  30. Y.H. Dai, C.X. Kou, A Nonlinear Conjugate Gradient Algorithm with An Optimal Property and An Improved Wolfe Line Search, SIAM Journal on Optimization, Vol. 23, No. 1, pp. 296-320, 2013.
  31. Y.H. Dai, A New Analysis on the Barzilai-Borwein Gradient Method, Journal of Operations Research Society of China, Vol. 1, No. 2, pp. 187-198, 2013.
  32. Y.N. Chen, Y.H. Dai, D. Han and W. Sun, Positive Semidefinite Generalized Diffusion Tensor Imaging via Quadratic Semidefinite Programming, SIAM Journal on Imaging Sciences, Vol. 6, No. 3, pp. 1531-1552, 2013.
  33. Y.F. Liu, M. Hong and Y.H. Dai, Max-Min Fairness Linear Transceiver Design Problem for a Multi-User SIMO Interference Channel Is Polynomial Time Solvable, IEEE Signal Processing Letters, Vol. 20, No. 1, pp. 27-30, 2013.
  34. Y.F. Liu, Y.H. Dai and Z.Q. Luo, Max-Min Fairness Linear Transceiver Design for a Multi-User MIMO Interference Channel, IEEE Transactions on Signal Processing, Vol. 61, No. 9, pp. 2413-2423, 2013.
  35. Y.F. Liu, Y.H. Dai and Z.Q. Luo, Joint Power and Admission Control via Linear Programming Deflation, IEEE Transactions on Signal Processing, Vol. 61, No. 6, pp. 1327-1338, 2013.
  36. B. Jiang and Y.H. Dai, Feasible Barzilai-Borwein-Like Methods for Extreme Symmetric Eigenvalue Problems, Optimization Methods and Software, Vol. 28, No. 4, pp.756-784, 2013.
  37. M.H. Cheng and Y.H. Dai, Adaptive Nonmonotone Spectral Residual Method for Large-scale Nonlinear Systems, Pacific Journal of Optimization, Vol. 8, No. 1, pp. 15-25, 2012.
  38. Y.H. Dai, A General Convergence Result for the BFGS Method, Computational Methods for Applied Inverse Problems (Ed. by Y. F. Wang, A. G. Yagola, C. C. Yang and W. de Gruyter), pp. 241-248, 2012.
  39. Y.H. Dai, Nonlinear Conjugate Gradient Methods, Wiley Encyclopedia of Operations Research and Management Science, DOI:10.1002/9780470400531.eorms0183, Published Online, 15 Feb, 2011.
  40. Y.H. Dai, Convergence of Conjugate Gradient Methods with Constant Stepsizes, Optimization Methods and Software, Vol. 26, No. 6, pp.895-909, 2011.
  41. Y.F. Liu, Y.H. Dai and Z.Q. Luo, Coordinated Beamforming for MISO Intereference Channel: Complexity Analysis and Efficient Algorithms, IEEE Transactions on Signal Processing, Vol. 59, No. 3, pp. 1142-1157, 2011.
  42. Y.F. Liu, Y.H. Dai and Z.Q. Luo, On the Complexity of Leakage Interference Minimization for Interference Alignment, in: Proc. IEEE 12th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 471-475, 2011.
  43. Y.F. Liu, Y.H. Dai and Z.Q. Luo, Max-Min Fairness Linear Transceiver Design for A Multi-User MIMO Interference Channel, in: Proc. IEEE International Conference on Communications, pp. 1-5, 2011.
  44. Y.H. Dai and N. Yamashita, Convergence Analysis of Sparse Quasi-Newton Updates with Positive Definite Matrix Completion for Two-Dimensional Functions, Numerical Algebra, Control and Optimization, Vol. 1, No. 1, pp. 61-69, 2011.
  45. Y.H. Dai, Convergence Analysis of Nonlinear Conjugate Gradient Methods, In: Optimization and Regularization for Computational Inverse Problems and Applications (Y.Wang, A.G.Yagola, C.Yang eds.), pp. 157-181, 2010.
  46. Y.F. Liu, Y.H. Dai and Z.Q. Luo, On the Complexity of Optimal Coordinated Downlink Beamforming, in: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 3274-3277, 2010.
  47. M.H. Cheng and Y.H. Dai, Sparse Two-Sided Rank-One Updates for Nonlinear Equations , Science in China, Series A Vol. 53, No. 11, pp. 2907-2915, 2010.
  48. Y.S. Fu and Y.H. Dai, Improved Projected Gradient Algorithms for Singly Linearly Constrained Quadratic Programs Subject to Lower and Upper Bounds , Asia-Pacific Journal of Operational Research, Vol. 27, No. 1, pp. 71-84, 2010.
  49. G.H. Yu, L. Q. Qi and Y.H. Dai, On Nonmonotone Chambolle Gradient Projection Algorithms for Total Variation Image Restoration, Journal of Mathematical Imaging and Vision, Vol. 35, No. 2, pp. 143-154, 2009.
  50. F. Li, Y. Fu, Y.H. Dai, C. Siminchisescu, J. Wang, Kernel Learning by Unconstrained Optimization, Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS), Clearwater Beach, Florida, USA, Volume 1 of JMLR: WCP5, pp.328-335, 2009.
  51. Y.H. Dai and K. Schittkowski, A Sequential Quadratic Programming Algorithm with Non-Monotone Line Search, Pacific Journal of Optimization, Vol. 4, No. 2, pp. 335-351, 2008.
  52. L.P. Wang and Y.H. Dai, Left Conjugate Gradient Methods for Non-Hermitian Linear Systems, Numerical Linear Algebra with Applications, Vol. 15, pp. 891-909, 2008.
  53. Z. Xu and Y.H. Dai, A Stochastic Approximation Frame Algorithm with Adaptive Directions, Numerical Mathematics-Theory Methods and Applications, Vol. 1, No. 4, pp. 460-474, 2008.
  54. Y.Q. Hu and Y.H. Dai, Inexact Barzilai-Borwein Method for Saddle Point Problems, Numerical Linear Algebra with Applications, Vol. 14, pp. 299-317, 2007.
  55. Y.H. Dai, Fast Algorithms on Projection on an Ellipsoid, SIAM Journal on Optimization, Vol. 16, No. 4, pp. 986-1006, 2006.
  56. Y.H. Dai and R. Fletcher, New Algorithms for Singly Linearly Constrained Quadratic Programs Subject to Lower and Upper Bounds, Mathematical Programming, Vol. 16, No. 3, pp. 403-421, 2006.
  57. Y.H. Dai and X.Q. Yang, A New Gradient Method with an Optimal Stepsize Property, Computational Optimization and Applications, Vol. 33, No. 1, pp. 73-88, 2006.
  58. Y.H. Dai, W.W. Hager, K. Schittkowski and H. C. Zhang, The Cyclic Barzilai-Borwein Method for Unconstrained Optimization, IMA Journal of Numerical Analysis, Vol. 26, No. 3, 604-627, 2006.
  59. B. Zhou, L. Gao and Y.H. Dai, Gradient Methods with Adaptive Step-Sizes, Computational Optimization and Applications, Vol. 35, No. 1, pp. 69-86, 2006.
  60. B. Zhou, L. Gao and Y.H. Dai, Monotone Projected Gradient Methods for Large-Scale Box-Constrained Quadratic Programming, Science in China, Series A, Vol. 36, No. 5, pp. 556-570, 2006.
  61. Y.H. Dai and R. Fletcher, On the Asymptotic Behaviour of Some New Gradient Methods, Mathematical Programming (Series A), Vol. 13, No. 3, pp. 541-559, 2005.
  62. Y.H. Dai and R. Fletcher, Projected Barzilai-Borwein Methods for Large-Scale Box-Constrained Quadratic Programming, Numerische Mathematik, Vol. 100, No. 1, pp. 21-47, 2005.
  63. Y.H. Dai and Y. Yuan, Analyses of Monotone Gradient Methods, Journal of Industry and Management Optimization, Vol. 1, No. 2, pp. 181-192, 2005.
  64. Y.H. Dai, L.Z. Liao, D. Li, An Analysis of Barzilai-Borwein Gradient Method for Unsymmetric Linear Equations, In: Optimization and control with applications (L. Qi, K. Teo and X. Yang, eds.), Springer, pp. 183-211, 2005.
  65. Y.H. Dai and J.Y. Yuan, Study on Semi-Conjugate Gradient Methods for Nonsymmetric Systems, International Journal of Numerical Methods in Engineering, Vol. 60, No. 8, pp. 1383-1399, 2004.
  66. Y.H. Dai, L.Z. Liao and D. Li, On Restart Procedures for The Conjugate Gradient Method, accepted by Applied Numerical Mathematics, Vol. 35, No. 2-4, pp. 249-261, 2004.
  67. Y.H. Dai, Alternate Step Gradient Method, Optimization, Vol. 52, No. 4-5, pp. 395-415, 2003.
  68. Y.H. Dai, A Family of Hybrid Conjugate Gradient Methods for Unconstrained Optimization, Mathematics of Computation, Vol. 72, pp. 1317-1328, 2003.
  69. Y.H. Dai and Y. Yuan, Alternate Minimization Gradient Method, IMA Journal of Numerical Analysis, Vol. 23, pp. 377-393, 2003.
  70. Y.H. Dai and Y. Yuan, A Class of Globally Convergent Conjugate Gradient Methods, Sciences in China (Series A), Vol. 46, No. 2, pp. 251-261, 2003.
  71. Y.H. Dai, Unified Convergence Analyses of Nonlinear Conjugate Gradient Methods, In: Numerical Linear Algebra and Optimization (Y. Yuan ed.), Science Press, Beijing/New York, pp. 3041, 2003.
  72. W.B. Liu, Y.H. Dai and J. Lamb, Novel supervisor-searcher cooperation algorithms for minimization problems with strong noise, Optimization Methods and Software, Vol. 18, pp. 246-264, 2003.
  73. Y.H. Dai and D.C. Xu, A New Family of Trust Region Algorithms for Unconstrained Optimization, Journal of Computational Mathematics, Vol. 21, No. 2, pp. 221-228, 2003.
  74. Y.H. Dai and Q. Ni, Testing Different Conjugate Gradient Methods for Large-Scale Unconstrained Optimization, Journal of Computational Mathematics, Vol. 21, No. 3, pp. 311-320, 2003.
  75. Y.H. Dai, J.M. Martinez and J.Y. Yuan, An Increasing-Angle Property of the Conjugate Gradient Method and the Implementation of Large-Scale Minimization Algorithms with Line Searches, Numerical Linear Algebra and Applications, Vol. 10, No. 4, pp. 323-334, 2003.
  76. Y.H. Dai, Convergence Properties of the BFGS algorithm, SIAM Journal on Optimization, Vol. 13, No. 3, pp. 693-701, 2002.
  77. Y.H. Dai and L.Z. Liao, $R$-Linear Convergence of the Barzilai and Borwein Gradient Method, IMA Journal of Numerical Analysis, Vol. 22, pp. 1-10, 2002.
  78. Y.H. Dai, On the Nonmonotone Line Search, Journal of Optimization Theory and Applications, Vol. 112, No. 2, pp. 315-330, 2002.
  79. Y.H. Dai, A Nonmonotone Conjugate Gradient Algorithm for Unconstrained Optimization, Journal of Systems Science and Complexity, Vol. 15, No. 2, pp. 139-145, 2002.
  80. Y.H. Dai, Conjugate Gradient Methods with Armijo-type Line Searches, Acta Mathematicae Applicatae Sinica (English Series), Vol. 18, No. 1, pp. 123-130, 2002.
  81. Y.H. Dai and Y. Yuan, A Note on the Nonlinear Conjugate Gradient Method, Journal of Computational Mathematics, Vol. 20, pp. 575-582, 2002.
  82. Y.H. Dai, J.Y. Yuan and Y. Yuan, Modified Two-point Stepsize Gradient Methods for Unconstrained Optimization, Computational Optimization and Applications, Vol. 22, pp. 103-109, 2002.
  83. Y.H. Dai and H.C. Zhang, An Adaptive Two-Point Stepsize Gradient Algorithm, Numerical Algorithms, Vol. 27, pp. 377-385, 2001.
  84. Y.H. Dai and Y. Yuan, An Extended Class of Nonlinear Conjugate Gradient Methods, In: D. Li eds. Proceedings of the 5th International Conference on Optimization: Techniques and Applications (December 2001, Hongkong), pp. 778-785, 2001.
  85. W.B. Liu and Y.H. Dai, Minimization Algorithms Based on Supervisor and Searcher Cooperation, Journal of Optimization Theory and Applications, Vol. 111, No. 2, pp. 359-379, 2001.
  86. Y.H. Dai and Y. Yuan, An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimization, Annals of Operations Research, Vol. 103, pp. 33-47, 2001.
  87. Y.H. Dai, Convergence of Nonlinear Conjugate Gradient Methods, Journal of Computational Mathematics, Vol. 19, No. 5, pp. 539-548, 2001.
  88. Y.H. Dai and Y. Yuan, A Three-parameter Family of Nonlinear Conjugate Gradient Methods, Mathematics of Computation, Vol. 70, pp. 1155-1167, 2001.
  89. Y.H. Dai and L.Z. Liao, New Conjugacy Conditions and Related Nonlinear Conjugate Gradient Methods , Applied Mathematics and Optimization, Vol. 43, No. 1, pp. 87-101, 2001.
  90. Y.H. Dai, New Properties of A Nonlinear Conjugate Gradient Method, Numerische Mathematics, Vol. 89, No. 1, pp. 83-98, 2001.
  91. Y.H. Dai and Y. Yuan, Nonlinear Conjugate Gradient Methods, Shanghai Scientific and Technical Publishers, Shanghai, China, 2000 (Monograph, in Chinese)
  92. Y.H. Dai, Some Properties of Memoryless Quasi-Newton Method, Journal on Numerical Methods and Computer Applications, Vol. 1, pp. 28-32, 2000.
  93. Y.H. Dai and Y. Yuan, Convergence of Three-term Conjugate Gradient Methods (in Chinese), Mathematica Numericia Sinica, Vol. 21, No. 3, pp. 355-362, 1999. (see Chinese Journal of Numerical Mathematics and Applications Vol. 21, No. 4, pp. 69-78, 1999 for English translation).
  94. Y.H. Dai, Further Insight Into the Convergence of the Fletcher-Reeves Method, Science in China (Series A) Vol. 42, No. 9, pp. 905-916, 1999.
  95. Y.H. Dai, J. Y. Han, G. H. Liu, D. F. Sun, H. X. Yin, and Y. Yuan, Convergence Properties of Nonlinear Conjugate Gradient Methods, SIAM Journal on Optimization, Vol. 10, No. 2, pp. 345-358, 1999.
  96. Y.H. Dai and Y. Yuan, A Nonlinear Conjugate Gradient Method with A Strong Global Convergence Property, SIAM Journal on Optimization, Vol. 10, No. 1, pp. 177-182, 1999.
  97. Y.H. Dai and Y. Yuan, Global Convergence of the Method of Shortest Residuals, Numerische Mathematik, Vol. 83, pp. 581-598, 1999.
  98. Y.H. Dai and Y. Yuan, Some Properties of A New Conjugate Gradient Method, in: Y. Yuan ed., Advances in Nonlinear Programming (Kluwer, Boston), pp. 251-262, 1998.
  99. Y.H. Dai and Y. Yuan, Convergence Properties of the Beale-Powell Restart Algorithm, Science in China, series A, Vol. 41, No. 11, pp. 1142-1150, 1998.
  100. Y.H. Dai and Y. Yuan, Convergence of the Fletcher-Reeves Method under A Generalized Wolfe Search (in Chinese), Numer. Math. J. Chinese Univ., Vol. 2, pp. 142-148, 1996.
  101. Y.H. Dai and Y. Yuan, Convergence Properties of the Conjugate Descent Method, Advances in Mathematics, Vol. 6, pp. 552-562, 1996.
  102. Y.H. Dai and Y. Yuan, Convergence Properties of the Fletcher-Reeves Method, IMA Journal of Numerical Analysis, Vol. 16, No. 2, pp. 155-164, 1996.