Steven R. Young

43 papers A 1B 2C 3Misc 1Journal 15Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Double-Edged Sword of Data-Driven Super-Resolution: Adversarial Super-Resolution Models. CoRR Haley Duba-Sullivan, Steven R. Young, Emma J. Reid
2024	—	`conf`	Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search. GECCO Companion Mark Coletti, Chathika Gunaratne, Steven R. Young, Swetha Varadarajan, Robert M. Patton, Thomas E. Potok
2022	C	`conf`	ICDARTS: Improving the Stability of Cyclic DARTS. ICMLA Emily J. Herron, Steven R. Young, Derek C. Rose
2022	—	`conf`	Neuromorphic Computing for Scientific Applications. RSDHA@SC 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
2022	J	`jnl`	Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators. IEEE Trans. Control. Syst. Technol. Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell
2021	—	`conf`	Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. ICONS 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
2021	C	`conf`	Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion. ACC Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell
2021	J	`jnl`	Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion. IEEE Control. Syst. Lett. Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell
2021	—	`conf`	Real-Time Evolution and Deployment of Neuromorphic Computing at The Edge. IGSC (Workshops) Catherine D. Schuman, Steven R. Young, Bryan P. Maldonado, Brian C. Kaul
2020	J	`jnl`	Accelerating Scientific Computing in the Post-Moore's Era. ACM Trans. Parallel Comput. Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Ryan S. Bennink, Neena Imam, Travis S. Humble
2020	—	`conf`	Ensembles of Networks Produced from Neural Architecture Search. ISC Workshops Emily J. Herron, Steven R. Young, Thomas E. Potok
2020	B	`conf`	Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. IJCNN 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
2020	J	`jnl`	Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. CoRR 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
2020	J	`jnl`	Inferring Convolutional Neural Networks' accuracies from their architectural characterizations. CoRR Duc Hoang, Jesse Hamer, Gabriel N. Perdue, Steven R. Young, Jonathan A. Miller, Anushree Ghosh
2020	—	`conf`	Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency. IGSC (Workshops) Catherine D. Schuman, Steven R. Young, J. Parker Mitchell, J. Travis Johnston, Derek C. Rose, Bryan P. Maldonado, Brian C. Kaul
2019	J	`jnl`	Deep Learning for Vertex Reconstruction of Neutrino-Nucleus Interaction Events with Combined Energy and Time Data. CoRR Linghao Song, Fan Chen, Steven R. Young, Catherine D. Schuman, Gabriel N. Perdue, Thomas E. Potok
2019	Misc	`conf`	Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data. ICASSP Linghao Song, Fan Chen, Steven R. Young, Catherine D. Schuman, Gabriel N. Perdue, Thomas E. Potok
2019	—	`conf`	Evolving Energy Efficient Convolutional Neural Networks. IEEE BigData Steven R. Young, Pravallika Devineni, Maryam Parsa, J. Travis Johnston, Bill Kay, Robert M. Patton, Catherine D. Schuman, Derek C. Rose, Thomas E. Potok
2019	—	`conf`	Exascale Deep Learning to Accelerate Cancer Research. IEEE BigData 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
2019	J	`jnl`	Exascale Deep Learning to Accelerate Cancer Research. CoRR Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz
2019	—	`conf`	Fine-Grained Exploitation of Mixed Precision for Faster CNN Training. MLHPC@SC Jeremy T. Johnston, Steven R. Young, Catherine D. Schuman, Junghoon Chae, Don D. March, Robert M. Patton, Thomas E. Potok
2019	C	`conf`	Inferring Convolutional Neural Networks' Accuracies from Their Architectural Characterizations. ICMLA Duc Hoang, Jesse Hamer, Gabriel N. Perdue, Steven R. Young, Jonathan A. Miller, Anushree Ghosh
2019	—	`conf`	Visualization System for Evolutionary Neural Networks for Deep Learning. IEEE BigData Junghoon Chae, Catherine D. Schuman, Steven R. Young, J. Travis Johnston, Derek C. Rose, Robert M. Patton, Thomas E. Potok
2018	A	`conf`	167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. SC 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
2018	J	`jnl`	A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers. ACM J. Emerg. Technol. Comput. Syst. 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
2018	J	`jnl`	Adiabatic Quantum Computation Applied to Deep Learning Networks. Entropy 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
2018	—	`conf`	Deepmod: An Over-the-Air Trainable Machine Modem for Resilient PHY Layer Communications. MILCOM Adam L. Anderson, Steven R. Young, Thomas P. Karnowski, Jason M. Vann
2018	—	`conf`	Neural Networks and Graph Algorithms with Next-Generation Processors. IPDPS Workshops Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Neena Imam, Travis S. Humble
2018	J	`jnl`	Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study. CoRR Drahomira Herrmannova, Steven R. Young, Robert M. Patton, Christopher G. Stahl, Nicole C. Kleinstreuer, Mary S. Wolfe
2017	J	`jnl`	A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. CoRR 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
2017	—	`conf`	Evolving Deep Networks Using HPC. MLHPC@SC 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
2017	—	`conf`	Neuromorphic computing for temporal scientific data classification. NCS Catherine D. Schuman, Thomas E. Potok, Steven R. Young, Robert M. Patton, Gabriel N. Perdue, Gangotree Chakma, Austin Wyer, Garrett S. Rose
2017	—	`conf`	Optimizing Convolutional Neural Networks for Cloud Detection. MLHPC@SC J. Travis Johnston, Steven R. Young, David Hughes, Robert M. Patton, Devin White
2017	B	`conf`	Vertex reconstruction of neutrino interactions using deep learning. IJCNN Adam M. Terwilliger, Gabriel N. Perdue, David Isele, Robert M. Patton, Steven R. Young
2016	—	`conf`	A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. MLHPC@SC 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
2015	J	`jnl`	A 1 TOPS/W Analog Deep Machine-Learning Engine With Floating-Gate Storage in 0.13 µm CMOS. IEEE J. Solid State Circuits Junjie Lu, Steven R. Young, Itamar Arel, Jeremy Holleman
2015	—	`conf`	Analog inference circuits for deep learning. BioCAS Jeremy Holleman, Itamar Arel, Steven R. Young, Junjie Lu
2015	—	`conf`	Optimizing deep learning hyper-parameters through an evolutionary algorithm. MLHPC@SC Steven R. Young, Derek C. Rose, Thomas P. Karnowski, Seung-Hwan Lim, Robert M. Patton
2014	—	`conf`	30.10 A 1TOPS/W analog deep machine-learning engine with floating-gate storage in 0.13μm CMOS. ISSCC Junjie Lu, Steven R. Young, Itamar Arel, Jeremy Holleman
2014	J	`jnl`	Hierarchical spatiotemporal feature extraction using recurrent online clustering. Pattern Recognit. Lett. Steven R. Young, Andrew S. Davis, Aaron Mishtal, Itamar Arel
2014	J	`jnl`	On the Impact of Approximate Computation in an Analog DeSTIN Architecture. IEEE Trans. Neural Networks Learn. Syst. Steven R. Young, Junjie Lu, Jeremy Holleman, Itamar Arel
2011	—	`conf`	Modeling Temporal Dynamics with Function Approximation in Deep Spatio-Temporal Inference Network. BICA Thomas P. Karnowski, Itamar Arel, Steven R. Young
2010	—	`conf`	A Fast and Stable Incremental Clustering Algorithm. ITNG Steven R. Young, Itamar Arel, Thomas P. Karnowski, Derek C. Rose