Gradient descent using duality structures T. Flynn preprint, 2018. pdf
Publications
SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning L. Li, S. Pandey, T. Flynn, N. Wheeler, and A. Hoisie ACM SIGMETRICS, 2022. pdf
A persistent adjoint method with dynamic time-scaling and an application to mass action kinetics T. Flynn Numerical Algorithms, vol. 89, 2022. 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
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