Steven R. Young

According to our database, Steven R. Young authored at least 37 papers between 2010 and 2024.

Collaborative distances:

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

2024

Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search.

Mark Coletti, Chathika Gunaratne, Steven R. Young, Swetha Varadarajan, Robert M. Patton, Thomas E. Potok

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2022

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators.

Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell

IEEE Trans. Control. Syst. Technol., 2022

Neuromorphic Computing for Scientific Applications.

Robert M. Patton, Prasanna Date, Shruti R. Kulkarni, Chathika Gunaratne, Seung-Hwan Lim, Guojing Cong, Steven R. Young, Mark Coletti, Thomas E. Potok, Catherine D. Schuman

Proceedings of the IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop, 2022

ICDARTS: Improving the Stability of Cyclic DARTS.

Emily J. Herron, Steven R. Young, Derek C. Rose

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

2021

Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion.

Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell

IEEE Control. Syst. Lett., 2021

Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach.

Maryam Parsa, Catherine D. Schuman, Nitin Rathi, Amirkoushyar Ziabari, Derek C. Rose, J. Parker Mitchell, J. Travis Johnston, Bill Kay, Steven R. Young, Kaushik Roy

Proceedings of the ICONS 2021: International Conference on Neuromorphic Systems 2021, 2021

Real-Time Evolution and Deployment of Neuromorphic Computing at The Edge.

Catherine D. Schuman, Steven R. Young, Bryan P. Maldonado, Brian C. Kaul

Proceedings of the 12th International Green and Sustainable Computing Workshops, 2021

2020

Accelerating Scientific Computing in the Post-Moore's Era.

Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Ryan S. Bennink, Neena Imam, Travis S. Humble

ACM Trans. Parallel Comput., 2020

Ensembles of Networks Produced from Neural Architecture Search.

Emily J. Herron, Steven R. Young, Thomas E. Potok

Proceedings of the High Performance Computing, 2020

Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment.

Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency.

Catherine D. Schuman, Steven R. Young, J. Parker Mitchell, J. Travis Johnston, Derek C. Rose, Bryan P. Maldonado, Brian C. Kaul

Proceedings of the 11th International Green and Sustainable Computing Workshops, 2020

2019

Fine-Grained Exploitation of Mixed Precision for Faster CNN Training.

Jeremy T. Johnston, Steven R. Young, Catherine D. Schuman, Junghoon Chae, Don D. March, Robert M. Patton, Thomas E. Potok

Proceedings of the 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2019

Inferring Convolutional Neural Networks' Accuracies from Their Architectural Characterizations.

Duc Hoang, Jesse Hamer, Gabriel N. Perdue, Steven R. Young, Jonathan A. Miller, Anushree Ghosh

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data.

Linghao Song, Fan Chen, Steven R. Young, Catherine D. Schuman, Gabriel N. Perdue, Thomas E. Potok

Proceedings of the IEEE International Conference on Acoustics, 2019

Evolving Energy Efficient Convolutional Neural Networks.

Steven R. Young, Pravallika Devineni, Maryam Parsa, J. Travis Johnston, Bill Kay, Robert M. Patton, Catherine D. Schuman, Derek C. Rose, Thomas E. Potok

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Exascale Deep Learning to Accelerate Cancer Research.

Robert M. Patton, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Visualization System for Evolutionary Neural Networks for Deep Learning.

Junghoon Chae, Catherine D. Schuman, Steven R. Young, J. Travis Johnston, Derek C. Rose, Robert M. Patton, Thomas E. Potok

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers.

Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Federico M. Spedalieri, Jeremy Liu, Ke-Thia Yao, Garrett S. Rose, Gangotree Chakma

ACM J. Emerg. Technol. Comput. Syst., 2018

Adiabatic Quantum Computation Applied to Deep Learning Networks.

Jeremy Liu, Federico M. Spedalieri, Ke-Thia Yao, Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Garrett S. Rose, Gangotree Chakma

Entropy, 2018

167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation.

Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Don D. March, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Thomas P. Karnowski, Maxim A. Ziatdinov, Sergei V. Kalinin

Proceedings of the International Conference for High Performance Computing, 2018

Deepmod: An Over-the-Air Trainable Machine Modem for Resilient PHY Layer Communications.

Adam L. Anderson, Steven R. Young, Thomas P. Karnowski, Jason M. Vann

Proceedings of the 2018 IEEE Military Communications Conference, 2018

Neural Networks and Graph Algorithms with Next-Generation Processors.

Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Neena Imam, Travis S. Humble

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, 2018

Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study.

Drahomira Herrmannova, Steven Robert Young, Robert M. Patton, Christopher G. Stahl, Nicole C. Kleinstreuer, Mary S. Wolfe

Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis, 2018

2017

Evolving Deep Networks Using HPC.

Steven R. Young, Derek C. Rose, J. Travis Johnston, William T. Heller, Thomas P. Karnowski, Thomas E. Potok, Robert M. Patton, Gabriel N. Perdue, Jonathan A. Miller

Proceedings of the Machine Learning on HPC Environments, 2017

Optimizing Convolutional Neural Networks for Cloud Detection.

J. Travis Johnston, Steven R. Young, David Hughes, Robert M. Patton, Devin White

Proceedings of the Machine Learning on HPC Environments, 2017

Neuromorphic computing for temporal scientific data classification.

Catherine D. Schuman, Thomas E. Potok, Steven R. Young, Robert M. Patton, Gabriel N. Perdue, Gangotree Chakma, Austin Wyer, Garrett S. Rose

Proceedings of the Neuromorphic Computing Symposium, 2017

Vertex reconstruction of neutrino interactions using deep learning.

Adam M. Terwilliger, Gabriel N. Perdue, David Isele, Robert M. Patton, Steven R. Young

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2015

A 1 TOPS/W Analog Deep Machine-Learning Engine With Floating-Gate Storage in 0.13 µm CMOS.

Junjie Lu, Steven R. Young, Itamar Arel, Jeremy Holleman

IEEE J. Solid State Circuits, 2015

Optimizing deep learning hyper-parameters through an evolutionary algorithm.

Steven R. Young, Derek C. Rose, Thomas P. Karnowski, Seung-Hwan Lim, Robert M. Patton

Proceedings of the Workshop on Machine Learning in High-Performance Computing Environments, 2015

Analog inference circuits for deep learning.

Jeremy Holleman, Itamar Arel, Steven R. Young, Junjie Lu

Proceedings of the IEEE Biomedical Circuits and Systems Conference, 2015

2014

On the Impact of Approximate Computation in an Analog DeSTIN Architecture.

Steven R. Young, Junjie Lu, Jeremy Holleman, Itamar Arel

IEEE Trans. Neural Networks Learn. Syst., 2014

Hierarchical spatiotemporal feature extraction using recurrent online clustering.

Steven R. Young, Andrew S. Davis, Aaron Mishtal, Itamar Arel

Pattern Recognit. Lett., 2014

30.10 A 1TOPS/W analog deep machine-learning engine with floating-gate storage in 0.13μm CMOS.

Junjie Lu, Steven R. Young, Itamar Arel, Jeremy Holleman

Proceedings of the 2014 IEEE International Conference on Solid-State Circuits Conference, 2014

2013

Recurrent Online Clustering as a Spatio-Temporal Feature Extractor in DeSTIN

Steven Robert Young, Itamar Arel

CoRR, 2013

2012

Recurrent Clustering for Unsupervised Feature Extraction with Application to Sequence Detection.

Steven Robert Young, Itamar Arel

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

2011

Modeling Temporal Dynamics with Function Approximation in Deep Spatio-Temporal Inference Network.

Thomas P. Karnowski, Itamar Arel, Steven R. Young

Proceedings of the Biologically Inspired Cognitive Architectures 2011, 2011

2010

A Fast and Stable Incremental Clustering Algorithm.

Steven R. Young, Itamar Arel, Thomas P. Karnowski, Derek C. Rose

Proceedings of the Seventh International Conference on Information Technology: New Generations, 2010