PUBLICATIONS OF Yu-Hong DAI

  1. Y.F. Liu and Y.H. Dai (2013), On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA Systems, Accepted for Publication in IEEE Transactions on Signal Processing.
  2. 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.
  3. Y.F. Liu, M. Hong, 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.
  4. 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.
  5. 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.
  6. 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.
  7. Y.H. Dai, A Perfect Example for the BFGS Method, Mathematical Programming, Vol. 138, No. 1-2, pp. 501-530, 2013.
  8. 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, 2012.
  9. 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.
  10. Y.H.Dai,W.W.Hager,K.Schittkowski and H.C.Zhang (2006), The cyclic Barzilai-Borwein method for unconstrained optimization, IMA Journal of Numerical Analysis, 26 (3): 604-627, 2006.
  11. Y.H. Dai (2004), Fast Algorithms on Projection on an Ellipsoid, University of Dundee Report NA/220 (Accepted by SIAM J. Optimization)
  12. L.P. Wang and Y.H. Dai (2004), ``Left Conjugate Gradient Method for Non-Hermitian Linear Systems", Research Report ICMSEC-2004-02, Academy of Mathematics and Systems Science, Chinese Academy of Sciences.
  13. Y.H. Dai and R. Fletcher (2003), New Algorithms for Singly Linearly Constrained Quadratic Programs Subject to Lower and Upper Bounds, University of Dundee Report NA/216 (Accepted by Math. Prog.)
  14. Y.H. Dai and R. Fletcher (2003), Projected Barzilai-Borwein Methods for Large-Scale Box-Constrained Quadratic Programming, Numerische Mathematik, Vol. 100, No. 1, pp. 21-47, 2005.
  15. Y.H. Dai and R. Fletcher (2003), On the Asymptotic Behaviour of Some New Gradient Methods, Mathematical Programming (Series A), Vol. 13, No. 3, pp. 541-559 (2005).
  16. Y.H. Dai and Y. Yuan (2005), Analyses of Monotone Gradient Methods, Journal of Industry and Management Optimization, Vol. 1, No. 2, pp. 181-192, 2005.
  17. Y.H. Dai and X.Q. Yang (2002), A New Gradient Method with an Optimal Stepsize Property, Research report (Accepted by Computational Optimization and Applications)
  18. 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.
  19. Y.H. Dai (2001), Alternate Step Gradient Method, Report AMSS-2001-041, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences. Published in: Optimization, Vol. 52, No. 4-5, pp. 395-415, 2003.
  20. Y.H. Dai (2001), Convergence of Polak-Ribi\`ere-Polyak Conjugate Gradient Method with Constant Stepsize, Research report AMSS-2001-040, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences.
  21. Y.H. Dai (2000), Convergence Analyses of Nonlinear Conjugate Gradient Methods, Report AMSS-2000-094, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences.
  22. Y.H. Dai, L.Z. Liao, and 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.
  23. 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.
  24. 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.
  25. 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.
  26. Y.H. Dai and Y. Yuan, Alternate Minimization Gradient Method, IMA Journal of Numerical Analysis, Vol. 23, pp. 377-393, 2003.
  27. 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.
  28. 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.
  29. Y.H. Dai and Y. Yuan, A Class of Globally Convergent Conjugate Gradient Methods, Report ICM-98-30, ICMSEC, Chinese Academy of Sciences. (Appeared in: Sciences in China (Series A), Vol. 46, No. 2, pp. 251-261, 2003)
  30. 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.
  31. Y.H. Dai, A Family of Hybrid Conjugate Gradient Methods for Unconstrained Optimization, Mathematics of Computation, Vol. 72, pp. 1317-1328, 2003.
  32. Y.H. Dai, Convergence Properties of the BFGS algorithm, SIAM Journal on Optimization, Vol. 13, No. 3, pp. 693-701, 2002.
  33. 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.
  34. Y.H. Dai and Y. Yuan, A Note on the Nonlinear Conjugate Gradient Method, to appear in: Journal of Computational Mathematics,Vol. 20, pp. 575-582, 2002.
  35. 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.
  36. 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.
  37. Y.H. Dai, On the Nonmonotone Line Search, Journal of Optimization Theory and Applications, Vol. 112, No. 2, pp. 315-330, 2002.
  38. 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.
  39. 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.
  40. Y.H. Dai and H. Zhang, An Adaptive Two-Point Stepsize Gradient Algorithm, Numerical Algorithms, Vol. 27, pp. 377-385, 2001.
  41. 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.
  42. 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.
  43. Y.H. Dai, Convergence of Nonlinear Conjugate Gradient Methods, Journal of Computational Mathematics, Vol. 19, No. 5, pp. 539-548, 2001.
  44. Y.H. Dai and Y. Yuan, A Three-parameter Family of Nonlinear Conjugate Gradient Methods, Mathematics of Computation, Vol. 70, pp. 1155-1167, 2001.
  45. 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.
  46. Y.H. Dai, New Properties of A Nonlinear Conjugate Gradient Metho', Numerische Mathematics, Vol. 89, No. 1, pp. 83-98, 2001.
  47. Y.H. Dai, Some Properties of Memoryless Quasi-Newton Method, Journal on Numerical Methods and Computer Applications, Vol. 1, pp. 28-32, 2000.
  48. Y.H. Dai and Y. Yuan, Nonlinear Conjugate Gradient Methods, Shanghai Scientific and Technical Publishers, Shanghai, China, 2000 (In Chinese)
  49. Y.H. Dai and Y. Yuan, Convergence Analyses 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).
  50. 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.
  51. 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.
  52. 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.
  53. Y.H. Dai and Y. Yuan, Global Convergence of the Method of Shortest Residuals, Numerische Mathematik, Vol. 83, pp. 581-598, 1999.
  54. 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.
  55. Y.H. Dai and Y. Yuan, Convergence Properties of the Beale-Powell Restart Algorithm, Sciences in China (series A), Vol. 41, No. 11, pp. 1142-1150, 1998.
  56. Y.H. Dai and Y. Yuan, Convergence of the Fletcher-Reeves Method under A Generalized Wolfe Search, Numer. Math. J. Chinese Univ., Vol. 2, pp. 142-148, 1996.
  57. Y.H. Dai and Y. Yuan, Convergence Properties of the Conjugate Descent Method, Advances in Mathematics, Vol. 6, pp. 552-562, 1996.
  58. 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.