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Thomas Flynn
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Year
Change Detection with the Kernel Cumulative Sum Algorithm
T Flynn, S Yoo
58th IEEE Conference on Decision and Control (CDC 2019), 2019
312019
Online algorithms for classification of urban objects in 3D point clouds
I Stamos, O Hadjiliadis, H Zhang, T Flynn
2012 Second International Conference on 3D Imaging, Modeling, Processing …, 2012
272012
Bounding the expected run-time of nonconvex optimization with early stopping
T Flynn, KM Yu, A Malik, N D'Imperio, S Yoo
UAI 2020, 2020
52020
Timescale separation in recurrent neural networks
T Flynn
Neural computation 27 (6), 1321-1344, 2015
42015
SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning
L Li, S Pandey, T Flynn, H Liu, N Wheeler, A Hoisie
Proceedings of the ACM on Measurement and Analysis of Computing Systems 6 (2 …, 2022
32022
Data Driven Stochastic Approximation For Change Detection
T Flynn, O Hadjiliadis, I Stamos, F Vázquez-Abad
Proceedings of the 2017 Winter Simulation Conference, 2017
32017
Convergence of one-step adjoint methods
T Flynn
22nd International Symposium on Mathematical Theory of Networks and Systems, 2016
32016
Online classification in 3D urban datasets based on hierarchical detection
T Flynn, O Hadjiliadis, I Stamos
2015 International Conference on 3D Vision, 380-388, 2015
32015
Stochastic Projective Splitting: Solving Saddle-Point Problems with Multiple Regularizers
PR Johnstone, J Eckstein, T Flynn, S Yoo
arXiv preprint arXiv:2106.13067, 2021
22021
Forward sensitivity analysis for contracting stochastic systems
T Flynn
Advances in Applied Probability 50 (1), 102-130, 2018
22018
Stochastic projective splitting
PR Johnstone, J Eckstein, T Flynn, S Yoo
Computational Optimization and Applications, 1-41, 2023
12023
Scalable deep learning-based microarchitecture simulation on GPUs
S Pandey, L Li, T Flynn, A Hoisie, H Liu
SC22: International Conference for High Performance Computing, Networking …, 2022
12022
A persistent adjoint method with dynamic time-scaling and an application to mass action kinetics
T Flynn
Numerical Algorithms 89 (1), 87-113, 2022
12022
A Simultaneous Perturbation Weak Derivative Estimator for Stochastic Neural Networks
T Flynn, F Vázquez-Abad
Computational Management Science 16, 715–738, 2019
12019
Gradient estimation for attractor networks
T Flynn
City University of New York, 2018
2018
Measure valued differentiation for stochastic neural networks
T Flynn
2017 Winter Simulation Conference (WSC), 4622-4623, 2017
2017
The duality structure gradient descent algorithm: analysis and applications to neural networks
T Flynn
arXiv preprint arXiv:1708.00523, 2017
2017
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Articles 1–17