Steven R. Young
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Optimizing Deep Learning Hyper-parameters Through an Evolutionary Algorithm
SR Young, DC Rose, TP Karnowski, SH Lim, RM Patton
Proceedings of the Workshop on Machine Learning in High-Performance …, 2015
A 1 TOPS/W Analog Deep Machine-Learning Engine With Floating-Gate Storage in 0.13 µm CMOS
J Lu, S Young, I Arel, Holleman, J.
IEEE Journal of Solid-State Circuits 50 (1), 270-281, 2015
A Fast and Stable Incremental Clustering Algorithm
S Young, I Arel, T Karnowski, D Rose
Information Technology: New Generations (ITNG), 2010 Seventh International …, 2010
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers
TE Potok, CD Schuman, SR Young, RM Patton, F Spedalieri, J Liu, ...
Proceedings of the Workshop on Machine Learning in High Performance …, 2016
Evolving Deep Networks Using HPC
SR Young, DC Rose, T Johnston, WT Heller, TP Karnowski, TE Potok, ...
Proceedings of the 3rd Workshop on Machine Learning in HPC Environments, 2017
167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation
RM Patton, JT Johnston, SR Young, CD Schuman, DD March, TE Potok, ...
Proceedings of the International Conference for High Performance Computing …, 2018
On the Impact of Approximate Computation in an Analog DeSTIN Architecture
S Young, J Lu, J Holleman, I Arel
IEEE transactions on neural networks and learning systems 25 (5), 934-946, 2014
Hierarchical Spatiotemporal Feature Extraction Using Recurrent Online Clustering
S Young, A Davis, A Mishtal, I Arel
Pattern Recognition Letters 37, 115-123, 2014
Adiabatic Quantum Computation Applied to Deep Learning Networks
J Liu, FM Spedalieri, KT Yao, TE Potok, C Schuman, S Young, R Patton, ...
Entropy 20 (5), 380, 2018
An Analog Online Clustering Circuit in 130nm CMOS
J Lu, S Young, I Arel, J Holleman
Solid-State Circuits Conference (A-SSCC), 2013 IEEE Asian, 177-180, 2013
Data mining for better material synthesis: The case of pulsed laser deposition of complex oxides
SR Young, A Maksov, M Ziatdinov, Y Cao, M Burch, J Balachandran, L Li, ...
Journal of Applied Physics 123 (11), 115303, 2018
Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment
GN Perdue, A Ghosh, M Wospakrik, F Akbar, DA Andrade, M Ascencio, ...
Journal of Instrumentation 13 (11), P11020, 2018
Vertex reconstruction of neutrino interactions using deep learning
AM Terwilliger, GN Perdue, D Isele, RM Patton, SR Young
2017 International Joint Conference on Neural Networks (IJCNN), 2275-2281, 2017
An Analysis of Image Storage Systems for Scalable Training of Deep Neural Networks
SH Lim, SR Young, RM Patton
The Seventh workshop on Big Data Benchmarks, Performance Optimization, and …, 2016
Neural Networks and Graph Algorithms with Next-Generation Processors
KE Hamilton, CD Schuman, SR Young, N Imam, TS Humble
2018 IEEE International Parallel and Distributed Processing Symposium …, 2018
Neuromorphic computing for temporal scientific data classification
CD Schuman, TE Potok, S Young, R Patton, G Perdue, G Chakma, ...
Proceedings of the Neuromorphic Computing Symposium, 2, 2017
Optimizing Convolutional Neural Networks for Cloud Detection
T Johnston, SR Young, D Hughes, RM Patton, D White
Proceedings of the 3rd Workshop on Machine Learning in HPC Environments, 4, 2017
Deepmod: An Over-the-Air Trainable Machine Modem for Resilient PHY Layer Communications
A Anderson, SR Young, TP Karnowski, JM Vann
MILCOM 2018-2018 IEEE Military Communications Conference (MILCOM), 213-218, 2018
Accelerating Scientific Computing in the Post-Moore’s Era
KE Hamilton, CD Schuman, SR Young, RS Bennink, N Imam, TS Humble
ACM Transactions on Parallel Computing (TOPC) 7 (1), 1-31, 2020
Deep Learning for Vertex Reconstruction of Neutrino-Nucleus Interaction Events with Combined Energy and Time Data
L Song, F Chen, SR Young, CD Schuman, G Perdue, TE Potok
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
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