YE,   QIANG

Professor
Department of Mathematics
University of Kentucky
Lexington, KY 40506-0027

Office:  735 Patterson Office Tower
Phone:  859-257-4653
Email:   qye3 “at” uky (dot) edu


Publications - Papers listed in MathSciNet.

  1. Orthogonal Gated Recurrent Unit with Neumann-Cayley Transformation (with V. Zadorozhnyy, E. Mucllari, C. Pospisil, and D. Nguyen), Neural Computation (to appear), arXiv:2208.06496
  2. Modeling imaged welding process dynamic behaviors using Generative Adversarial Network (GAN) for a new foundation to monitor weld penetration using deep learning, (with Edison Mucllari, Yue Cao, and YuMing Zhang), Journal of Manufacturing Processes, 124 (2024): 187-195.
  3. Breaking Time Invariance: Assorted-Time Normalization for RNNs, (with Cole Pospisil and Vasily Zadorozhnyy), Neural Processing Letters, 56, 78 (2024), https://doi.org/10.1007/s11063-024-11442-1.
  4. SCP-GAN: Self-Correcting Discriminator Optimization for Training Consistency Preserving Metric GAN on Speech Enhancement Tasks, (with V. Zadorozhnyy and K. Koishida), Proc. INTERSPEECH 2023, doi: 10.21437/Interspeech.2023-456.
  5. Do We Need a New Foundation to Use Deep Learning to Monitor Weld Penetration? (with Edison Mucllari, Rui Yu, Yue Cao, and YuMing Zhang) , IEEE Robotics and Automation Letters, vol. 8, no. 6, pp. 3669-3676, June 2023.
  6. Novel Molecular Representations using Neumann-Cayley Orthogonal Gated Recurrent Unit, (with E. Mucllari, V. Zadorozhnyy, and D. Nguyen) , Journal of Chemical Information and Modeling, 2023, 63, 9, 2656–2666.
  7. Batch Normalization Preconditioning for Stochastic Gradient Langevin Dynamics, (with Susanna Lange, Wei Deng, and Guang Lin) , Journal of Machine Learning, 2(1): 65- 82, 2023.
  8. Deep Learning Based Real-Time and In-Situ Monitoring of Weld Penetration: Where we are and what are needed revolutionary solutions? (with Rui Yu, Yue Cao, Heping Chen, and YuMing Zhang), Journal of Manufacturing Processes, 93 (2023): 15–46.
  9. Accelerated Sparse Recovery via Gradient Descent with Nonlinear Conjugate Gradient Momentum, (with M. Hu, Y. Lou, B. Wang, M. Yan, and X. Yang) , Journal of Scientific Computing, (2023) 95:33.
  10. A method for computing a few eigenpairs of large generalized eigenvalue problems, (with Maged Alkilayh and Lothar Reichel) , Applied Numerical Mathematics, Volume 183, 2023, Pages 108-117.
  11. AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows, (with Yuliang Ji, Difeng Cai, Huan He, and Yuanzhe Xi), The 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022), 2022.
  12. Batch Normalization Preconditioning for Neural Network Training, (with Susanna Lange and Kyle Helfrich), arXiv:2108.01110., Journal of Machine Learning Research, 23(72):1-41, 2022.
  13. Symmetry-Structured Convolutional Neural Networks, (with K.D. Gayan Maduranga and Vasily Zadorozhnyy), arXiv:2203.02056., Neural Computing and Applications.35, 4421–4434 (2023).
  14. Stochastic Gradient Descent with Nonlinear Conjugate Gradient-Style Adaptive Momentum, (with Bao Wang), arXiv:2012.02188. IEEE Transactions on Neural Networks and Learning Systems. 2023
  15. FiberSim: a flexible open-source model of myofilament-level contraction, (with S. Kosta, D. Colli, and K. S. Campbell), Biophysical Journal, DOI:https://doi.org/10.1016/j.bpj.2021.12.021.
  16. Adaptive Weighted Discriminator for Training Generative Adversarial Networks, (with Vasily Zadorozhnyy and Qiang Cheng), arXiv:2012.03149. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, pp. 4781-4790.
  17. A Robust Deep Learning Approach for Automatic Classification of Seizures Against Non-Seizures, (with Xinghua Yao, Xiaojin Li, Yan Huang, Qiang Cheng and Guo-Qiang Zhang), Biomedical Signal Processing and Control, 64(2021):102215.
  18. Eigenvalue Normalized Recurrent Neural Networks for Short Term Memory, (with K. Helfrich), (arXiv:1911.07964), Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, Vol 34 No 04: Pages 4115-4122, 2020.
  19. Improving RNA secondary structure prediction via state inference with deep recurrent neural networks, (with D. Willmott and D. Murrugarra), (arXiv:1906.10819). Computational and Mathematical Biophysics, 8(2020):36-50.
  20. On Regularization of Convolutional Kernel Tensors in Neural Networks, (with Peichang Guo) (arXiv:1906.04866), Linear and Multilinear Algebra, 2020.
  21. Preconditioning for Accurate Solutions of Ill-Conditioned Linear Systems, arXiv:1705.04340 [math.NA], Numerical Linear Algebra with Applications, 27(2020):e2315.
  22. Complex Unitary Recurrent Neural Networks using Scaled Cayley Transform, (with K.D. Maduranga and K. Helfrich), arXiv:1811.04142 [stat.ML], Proceedings of the Thirty-Third AAAI (Association for the Advancement of Artificial Intelligence) Conference on Artificial Intelligence, Vol 33 No 01: Pages 4528-4535, 2019.
  23. Orthogonal Recurrent Neural Networks with Scaled Cayley Transform, (with K. Helfrich and D. Willmott), arXiv:1705.09520 [stat.ML], Proceedings of the 35th International Conference on Machine Learning, ICML 2018, PMLR 80:1969-1978, 2018.
  24. Error Bounds for the Krylov Subspace methods for Computations of Matrix Exponentials, (with H. Wang), (arXiv:1603.07358 [math.NA]), SIAM J. Matrix Anal. Appl., 38(1), 155–187.
  25. Accurate Inverses for Computing Eigenvalues of Extremely Ill-Conditioned Matrices and Differential Operators, arXiv:1512.05292 [math.NA], Math. Comp. 87 (2018), 237-259
  26. Deflation by restriction for the inverse-free preconditioned Krylov subspace method , (with Q. Liang), Numerical Algebra, Control and Optimization, 6(2016): 55 - 71.
  27. Outlier Detection in the Framework of Dimensionality Reduction , (with W. Zhi), Int. J. Patt. Recogn. Artif. Intell. , 29 (2015):1550017 [19 pages].
  28. Discrete Hessian Eigenmap Algorithm for Dimensionality Reduction , (with W. Zhi), J. Comp. Applied Math., 278(2015):197–212.
  29. Computing Singular Values of Large Matrices With Inverse Free Preconditioned Krylov Subspace Method , (with Q. Liang), Electron. Trans. Numer. Anal.,, 42(2014):197-221.
  30. Relative perturbation theory for diagonally dominant matrices, (with M. Dailey and F. M. Dopico), SIAM J. Matrix Anal. Appl.,, 35(2014), 1303–1328.
  31. New relative perturbation bounds for LDU factorizations of diagonally dominant matrices, (with M. Dailey and F. M. Dopico), SIAM J. Matrix Anal. Appl.,, 35(2014), 904–930.
  32. Simultaneous Similarity Reductions for a Pair of Matrices to Condensed Forms (with R.C. Li), Comm. Math. Statis., 2(2014):139-153.
  33. Computing Exponentials of Essentially Non-negative Matrices Entrywise to High Relative Accuracy (with J. Xue), Math. Comp.,, 82 (2013), 1577-1596.
  34. Analysis of Alignment Algorithms with Mixed Dimensions for Dimensionality Reduction, (with W. Zhi) Numer. Linear Algebra Appl., 20(2013):369-384.
  35. Error Bounds for the Lanczos Methods for Approximating Matrix Exponentials, SIAM J. Numer. Anal. 51(2013), 68–87
  36. Infinite matrices bounded on weighted L1 spaces, (with J. Williams) Linear Algebra Appl. 438 (2013), no. 12, 4689–4700.
  37. Eigenvalue Bounds for an Alignment Matrix in Manifold Learning (with W. Zhi), Linear Algebra and its Applications, 436(2012):2944–2962.
  38. Tikhonov regularization based on generalized Krylov subspace methods (with L. Reichel and F. Sgallari), Applied Numerical Mathematics 62 (2012) : 1215–1228
  39. Inexact Subspace Iterations For the Generalized Eigenvalue Problems (with P. Zhang), Linear Algebra and its Applications, 434 (2011):1697-1715.
  40. Alignments of Manifold Sections of Different Dimensions in Manifold Learning, (with W. Zhi), Proceedings of AAAI Fall 2010 Symposium on Manifold Learning and Its Applications, November, 2010, Arlington, VA, vol. 6, pp.63-68.
  41. A Block Inverse-free Preconditioned Krylov Subspace Method for Symmetric Generalized Eigenvalue Problems (with P. Quillen), J. Comp. Applied Math 233(2010):1298-1313
  42. Relative Perturbation Bounds for Eigenvalues of Diagonally Dominant Matrices, SIAM J. Matrix Anal. Appl. 31(2009):11-17.
  43. Simple square smoothing regularization operators (with L. Reichel) Electron. Trans. Numer. Anal. 33 (2008/09), 63–83.
  44. Entrywise Relative Perturbation Bounds for Exponentials of Essentially Nonnegative Matrices, (with J. Xue), Numer. Math. 110(2008):393--403.
  45. Computing Singular Values of Diagonally Dominant Matrices to High Relative Accuracy,  Math. Comp. 77(2008), 2195-2230. (Erratum for Theorem 3 in the case of the column diagonal dominance pivoting.)
  46. A Generalized LSQR Algorithm, (with L. Reichel),  Numer. Linear Algebra Appl. 15(2008) : 643-660.
  47. Optimal Expansion of Subspaces for Eigenvector Approximations,  Linear Algebra Appl. 428(2008): 911-918.
  48. Analysis of an Algnment Algorithm for Nonlinear Dimensionality Reduction (with H. Zha, R.C. Li), BIT - Numerical Mathematics, 47, 2007: 873-885.
  49. Eigenvalues of An Alignment Matrix in Nonlinear Manifold Learning, (with C. Li, R.C. Li),   Comm.  Math. Sciences, 5(2007):313-329.
  50. Improving the Uniqueness of Surface Wave Inversion Using Multiple-Mode Dispersion Data, (with Y. Supranata, M. Kalinski), ASCE International Journal of Geomechanics 7 (2007): 333-343.
  51. Krylov type subspace methods for matrix polynomials, (with L. Hoffnung and R.C. Li ), Linear Algebra Appl., 415 (2006):52–81.
  52. An Iterated Shift-and-invert Arnoldi Algorithm for  Quadratic Matrix Eigenvalue Problems, Applied Math. Comp. 172(2006):818-827.
  53. Algorithm 845: EIGIFP: A MATLAB Program for Solving Large Symmetric Generalized Eigenvalue Problems, (with James Money), ACM Transaction on Mathematical Softwares, 31(2005):270-279.
  54. Breakdown-free GMRES for Singular Systems, (with L. Reichel), SIAM J.  Matrix Anal. Appl., 26(2005):1001 – 1021.
  55. A Krylov subspace method  for quadratic matrix polynomials with application  to constrained least squares problems, (with R.C. Li),  SIAM J.  Matrix Analysis Appl., 25 (2003):405-428.
  56. An inverse free preconditioned  krylov subspace method for symmetric generalized eigenvalue problems (with G. Golub),  SIAM J. Sci. Comp.  24 (2002):312-334.
  57. Entrywise perturbation theory for diagonally dominant M-matrices with applications, (with A. Alfa, J. Xue), Numer. Math.  90 (2002):401-414.
  58. Accurate computation for the smallest eigenvalue of a diagonally dominant M-matrices, (with A. Alfa, J. Xue),   Math. Comp.  71 (2002):217-236.
  59. Accurate Estimate of Spectral Radii of Rate Matrices  of GI/M/1 Type Markov Chains, Matrix-Analytic Methods, Theory and Applications , G. Latouche and P.G. Taylor (Editors), 2002, World Scientific, NJ. pp. 403-416.
  60. On Latouche-Ramaswami's Logarithmic Reduction Algorithm for Quasi-birth-and-death Processes,  Stoch. Models, 18 (2002):449-467. (Awarded the Marcel F. Neuts Prize.)
  61. Inexact Inverse Iterations for the Generalized Eigenvalue Problems, (with G. Golub), BIT - Numerical Mathematics,  40 (2000): 672-684.
  62. Perturbation theory for the asymptotic decay rates in  the queues with Markovian arrival process,  (with A. Alfa, J.Xue),  Queueing Systems - Theory and Applications 36 (2000):287-301.
  63. High accuracy algorithms for solving nonlinear matrix equations in queueing models, Advances in Algorithmic Methods for Stochastic Models -  Proceedings of the 3rd International Conference on Matrix Analytic Methods, G. Latouche and P.G. Taylor (Editors),  2000, Notable Publications Inc. NJ. pp. 401-415.
  64. Entrywise perturbation theory for rate matrices of GI/M/1 type Markov chains, (with A. Alfa, J. Xue),  Stoch. Models 16 (2000):361-375.
  65. Residual Replacement Strategies for Krylov Subspace Iterative Methods for the Convergence of True Residuals, (with H. van der Vorst), SIAM J. Sci. Comp 22 (2000):836-852.
  66. Inexact preconditioned conjugate gradient method with inner-outer iteration, (with   G. Golub), SIAM J. Sci. Comp. 21 (2000):1305-1320.
  67. Analysis of finite precision bi-conjugate gradient algorithm for nonsymmetric linear systems, (with Charles Tong),  Math. Comp. 69 (2000):1559-1575.
  68. An analysis of groundwater flow in an infinite region with a sinusoidal top, (with  P.N. Shivakumar, J.J. Williams, C. Ji), Numer. Funct. Anal. Optim. 21 (2000):263-271.
  69. ABLE: an Adaptive Block Lanczos Method for Non-Hermitian Eigenvalue  Problems, (with Z. Bai and D. Day), SIAM J. Matrix  Anal. Appl.  20 (1999):1060-1082.
  70. A variational principle for eigenvalues of pencils of Hermitian matrices, (with P. Binding, B. Najman), Integral Equations and Operator Theory,  35 (1999): 398-422.
  71. Error Bound for Reduced System Model by Pade Approximation Via the  Lanczos Process, (with Z. Bai, R. Slone, W. Smith), IEEE Trans. on Computer-Aided Design 18 (1999):133-141.
  72. Error Estimation of the Pade Approximation of Transfer Functions Via the Lanczos Process,  (with Z. Bai), Electronic Transaction of  Numerical Analysis, 7 (1998):1-17.
  73. A Mixed Product Krylov Subspace method for Solving Nonsymmetric Linear Systems, (with T. F. Chan), Asian J. Math. 1 (1997):422-434.
  74. A linear system solver based on a modified Krylov subspace method for breakdown recovery, (with Charles Tong), Numer. Alg. 12 (1996):233-251.
  75. On two-sided bounds related to weakly diagonally dominant M-matrices with applications to digital circuit dynamics, (with  P.N. Shivakumar, J.J. Williams, C. Marinov), SIAM J. Matrix Anal. Appl. 17(1996):298-312.
  76. Bounds for the width of the instability intervals in the Mathieu equation, (with    P.N. Shivakumar),  Operator Theory: Advances and Applications vol.87, Birkhauser, Basel, 1996, pp. 348 - 357.
  77. An adaptive block Lanczos algorithm, Numer. Alg. 12 (1996):97-110.
  78. On  close  eigenvalues  of  tridiagonal matrices, Numer. Math. 70 (1995):507-514.
  79. Variational principles for indefinite eigenvalue problems, (with P.A. Bining), Linear Algebra Appl. 218 (1995):251-262
  80. A breakdown-free variation of the nonsymmetric Lanczos algorithms, Math. Comp. 62 (1994):179-207.
  81. Low rank perturbations of strongly definitizable transformations and matrix polynomials,  (with P. Lancaster, A. Marcus), Linear Algebra and Appl. 198 (1994):3-29.
  82. Strongly definitizable linear pencils in Hilbert space,  (with P. Lancaster, A. Shkalikov), Integral Equations Operator Theory, 17 (1993):338-360.
  83. Rayleigh-Ritz and Lanczos methods for symmetric matrix pencils, (with P. Lancaster), Linear Algebra Appl. 185 (1993):173-201.
  84. Definitizable hermitian matrix pencils,  (with P. Lancaster),  Aequationes Mathematicae 46  (1993):44-55.
  85. A minimax characterization for eigenvalues of Hermitian pencils II (with B. Najman), Linear Algebra Appl. 191 (1993):183-197.
  86. Some general variational principles, (with P. A. Binding), Proc. Amer. Math. Soc. 114 (1992):107-114
  87. A convergence analysis of nonsymmetric Lanczos algorithms,  Math. Comp. 56 (1991):677-691.
  88. Variational principles without definiteness conditions,  (with P. Binding), SIAM J.  Math.  Anal.  22 (1991):1575-1583
  89. A minimax characterization for eigenvalues of hermitian pencils, (with B. Najman), Linear Alg. Appl. 144 (1991):217-230
  90. Variational and numerical methods for symmetric matrix pencils,  (with P. Lancaster), Bulletin of  Austr. Math. Soc. 43(1991):1-17
  91. Variational properties and Rayleigh quotient algorithms for symmetric matrix pencils (with P. Lancaster),  in Operator Theory: Advances and Applications, vol.40, The Gohberg Anniversary Collection, Birkhauser, Basel, 1989, pp.247-278.
  92. Variational principles and numerical algorithms for symmetric matrix pencils, Ph.D. Thesis, University of Calgary, Calgary, Canada, 1989.
  93.  Inverse spectral problems for linear and quadratic matrix pencils, (with P. Lancaster) Linear Alg.Appl. 107 (1988):293-309.
  94. The unsolvability of inverse eigenvalue problems for hermitian matrices almost everywhere, Math. Numer. Sinica, 9(1987):225-232.
  95. A class of iterative algorithms for solving inverse eigenvalue problems, Math. Numer. Sinica, 9(1987):144-153.
  96. The unsolvability of inverse algebraic eigenvalue problems almost everywhere, (with J.G. Sun), J. Comp.  Math.  4 (1986):212-236