Thomas Flynn

According to our database, Thomas Flynn authored at least 22 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Correction to: Stochastic projective splitting.

Patrick R. Johnstone, Jonathan Eckstein, Thomas Flynn, Shinjae Yoo

Comput. Optim. Appl., March, 2024

Stochastic projective splitting.

Patrick R. Johnstone, Jonathan Eckstein, Thomas Flynn, Shinjae Yoo

Comput. Optim. Appl., March, 2024

An Evaluation of Real-time Adaptive Sampling Change Point Detection Algorithm using KCUSUM.

Vijayalakshmi Saravanan, Perry Siehien, Shinjae Yoo, Hubertus Van Dam, Thomas Flynn, Christopher Kelly, Khaled Z. Ibrahim

CoRR, 2024

2023

Learning Independent Program and Architecture Representations for Generalizable Performance Modeling.

Lingda Li, Thomas Flynn, Adolfy Hoisie

CoRR, 2023

EXARL-PARS: Parallel Augmented Random Search Using Reinforcement Learning at Scale for Applications in Power Systems.

Himanshu Sharma, Joshua D. Suetterlein, Sumathi Lakshmiranganatha, Thomas Flynn, Draguna L. Vrabie, Christine Sweeney, Vinay Ramakrishniah

Proceedings of the Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023

2022

SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning.

Lingda Li, Santosh Pandey, Thomas Flynn, Hang Liu, Noel Wheeler, Adolfy Hoisie

Proc. ACM Meas. Anal. Comput. Syst., 2022

A persistent adjoint method with dynamic time-scaling and an application to mass action kinetics.

Thomas Flynn

Numer. Algorithms, 2022

Scalable Deep Learning-Based Microarchitecture Simulation on GPUs.

Santosh Pandey, Lingda Li, Thomas Flynn, Adolfy Hoisie, Hang Liu

Proceedings of the SC22: International Conference for High Performance Computing, 2022

2021

Stochastic Projective Splitting: Solving Saddle-Point Problems with Multiple Regularizers.

Patrick R. Johnstone, Jonathan Eckstein, Thomas Flynn, Shinjae Yoo

CoRR, 2021

SimNet: Computer Architecture Simulation using Machine Learning.

Lingda Li, Santosh Pandey, Thomas Flynn, Hang Liu, Noel Wheeler, Adolfy Hoisie

CoRR, 2021

2020

Bounding the expected run-time of nonconvex optimization with early stopping.

Thomas Flynn, Kwangmin Yu, Abid Malik, Nicholas D'Imperio, Shinjae Yoo

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Layered SGD: A Decentralized and Synchronous SGD Algorithm for Scalable Deep Neural Network Training.

Kwangmin Yu, Thomas Flynn, Shinjae Yoo, Nicholas D'Imperio

CoRR, 2019

A simultaneous perturbation weak derivative estimator for stochastic neural networks.

Thomas Flynn, Felisa J. Vázquez-Abad

Comput. Manag. Sci., 2019

Change Detection with the Kernel Cumulative Sum Algorithm.

Thomas Flynn, Shinjae Yoo

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

Gradient Estimation for Attractor Networks.

Thomas Flynn

PhD thesis, 2018

2017

Gradient Descent using Duality Structures.

Thomas Flynn

CoRR, 2017

Data driven stochastic approximation for change detection.

Thomas Flynn, Olympia Hadjiliadis, Ioannis Stamos, Felisa J. Vázquez-Abad

Proceedings of the 2017 Winter Simulation Conference, 2017

Measure valued differentiation for stochastic neural networks.

Thomas Flynn

Proceedings of the 2017 Winter Simulation Conference, 2017

2016

Forward sensitivity analysis for contracting stochastic systems.

Thomas Flynn

CoRR, 2016

2015

Timescale Separation in Recurrent Neural Networks.

Thomas Flynn

Neural Comput., 2015

Online Classification in 3D Urban Datasets Based on Hierarchical Detection.

Thomas Flynn, Olympia Hadjiliadis, Ioannis Stamos

Proceedings of the 2015 International Conference on 3D Vision, 2015

2012

Online Algorithms for Classification of Urban Objects in 3D Point Clouds.

Ioannis Stamos, Olympia Hadjiliadis, Hongzhong Zhang, Thomas Flynn

Proceedings of the 2012 Second International Conference on 3D Imaging, 2012