Preprints and Publications

Preprints

  • Gradient descent using duality structures
    T. Flynn
    preprint, 2018. pdf

Publications

  • A persistent adjoint method with dynamic time-scaling and an application to mass action kinetics T. Flynn. Numerical Algorithms (forthcoming) pdf
  • Bounding the expected run-time of nonconvex optimization with early stopping
    T. Flynn, K. M. Yu, A. Malik, N. D’Imperio, and S. Yoo
    36th Conference on Uncertainty in Artificial Intelligence, Aug. 3-6, 2020 pdf
  • A Simultaneous Perturbation Weak Derivative Estimator for Stochastic Neural Networks
    T. Flynn and F. J. Vázquez-Abad
    Computational Management Science, vol. 16, no. 4., 2019. pdf
  • Change detection with the kernel cumulative sum algorithm
    T. Flynn and S. Yoo
    58th IEEE Conference on Decision and Control (CDC), Nice. Dec. 11-13, 2019. pdf
  • Forward sensitivity analysis for contracting stochastic systems
    T. Flynn
    Advances in Applied Probability 50:1, 102–130, 2018. pdf
  • Data driven stochastic approximation for change detection
    T. Flynn, O. Hadjiliadis, I. Stamos, and F. J. Vázquez-Abad
    Proceedings of the 2017 Winter Simulation Conference, Las Vegas, Dec. 3-6, 2017. pdf
  • Convergence of one-step adjoint methods
    T. Flynn
    22nd International Symposium on Mathematical Theory of Networks and Systems, Minneapolis, USA, July 12-15, 2016. pdf
  • Online Classification in 3D Urban Datasets Based on Hierarchical Detection
    T. Flynn, O. Hadjiliadis, and I. Stamos
    International Conference on 3D Vision (3DV), Lyon, Oct. 19-22, 2015. pdf
  • Time-scale separation in recurrent neural networks
    T. Flynn
    Neural Computation 27:6, 1321-1344, 2015. pdf
  • Online algorithms for classification of urban objects in 3D point clouds
    I. Stamos, O. Hadjiliadis, H. Zhang, and T. Flynn
    The second 3DIMPVT Conference, Zürich, Switzerland, Oct. 13-15, 2012. pdf