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2020 – today
- 2024
[c30]Mark Coletti
, Chathika Gunaratne, Steven R. Young, Swetha Varadarajan, Robert M. Patton, Thomas E. Potok:
Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search. GECCO Companion 2024: 1888-1894- 2022
- [j8]Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell:
Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators. IEEE Trans. Control. Syst. Technol. 30(6): 2433-2449 (2022) - [c29]Emily J. Herron, Steven R. Young, Derek C. Rose:
ICDARTS: Improving the Stability of Cyclic DARTS. ICMLA 2022: 1055-1062 - [c28]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:
Neuromorphic Computing for Scientific Applications. RSDHA@SC 2022: 22-28 - 2021
- [j7]Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell:
Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion. IEEE Control. Syst. Lett. 5(6): 2204-2209 (2021) - [c27]Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell:
Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion. ACC 2021: 1830-1835 - [c26]Catherine D. Schuman, Steven R. Young, Bryan P. Maldonado, Brian C. Kaul:
Real-Time Evolution and Deployment of Neuromorphic Computing at The Edge. IGSC (Workshops) 2021: 1-8 - [c25]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:
Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. ICONS 2021: 14:1-14:8 - 2020
- [j6]Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Ryan S. Bennink, Neena Imam, Travis S. Humble:
Accelerating Scientific Computing in the Post-Moore's Era. ACM Trans. Parallel Comput. 7(1): 6:1-6:31 (2020) - [c24]Catherine D. Schuman, Steven R. Young, J. Parker Mitchell, J. Travis Johnston, Derek C. Rose, Bryan P. Maldonado, Brian C. Kaul:
Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency. IGSC (Workshops) 2020: 1-8 - [c23]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:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. IJCNN 2020: 1-9 - [c22]Emily J. Herron, Steven R. Young, Thomas E. Potok:
Ensembles of Networks Produced from Neural Architecture Search. ISC Workshops 2020: 223-234 - [i7]Duc Hoang, Jesse Hamer, Gabriel N. Perdue, Steven R. Young, Jonathan A. Miller, Anushree Ghosh:
Inferring Convolutional Neural Networks' accuracies from their architectural characterizations. CoRR abs/2001.02160 (2020) - [i6]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:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. CoRR abs/2005.04171 (2020)
2010 – 2019
- 2019
- [c21]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:
Exascale Deep Learning to Accelerate Cancer Research. IEEE BigData 2019: 1488-1496 - [c20]Steven R. Young, Pravallika Devineni, Maryam Parsa, J. Travis Johnston, Bill Kay, Robert M. Patton, Catherine D. Schuman, Derek C. Rose, Thomas E. Potok:
Evolving Energy Efficient Convolutional Neural Networks. IEEE BigData 2019: 4479-4485 - [c19]Junghoon Chae, Catherine D. Schuman, Steven R. Young, J. Travis Johnston, Derek C. Rose, Robert M. Patton, Thomas E. Potok:
Visualization System for Evolutionary Neural Networks for Deep Learning. IEEE BigData 2019: 4498-4502 - [c18]Linghao Song, Fan Chen, Steven R. Young, Catherine D. Schuman, Gabriel N. Perdue, Thomas E. Potok:
Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data. ICASSP 2019: 3882-3886 - [c17]Duc Hoang, Jesse Hamer, Gabriel N. Perdue, Steven R. Young, Jonathan A. Miller, Anushree Ghosh:
Inferring Convolutional Neural Networks' Accuracies from Their Architectural Characterizations. ICMLA 2019: 1388-1391 - [c16]Jeremy T. Johnston, Steven R. Young, Catherine D. Schuman, Junghoon Chae, Don D. March, Robert M. Patton, Thomas E. Potok:
Fine-Grained Exploitation of Mixed Precision for Faster CNN Training. MLHPC@SC 2019: 9-18 - [i5]Linghao Song, Fan Chen, Steven R. Young, Catherine D. Schuman, Gabriel N. Perdue, Thomas E. Potok:
Deep Learning for Vertex Reconstruction of Neutrino-Nucleus Interaction Events with Combined Energy and Time Data. CoRR abs/1902.00743 (2019) - [i4]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:
Exascale Deep Learning to Accelerate Cancer Research. CoRR abs/1909.12291 (2019) - 2018
- [j5]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:
Adiabatic Quantum Computation Applied to Deep Learning Networks. Entropy 20(5): 380 (2018) - [j4]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:
A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers. ACM J. Emerg. Technol. Comput. Syst. 14(2): 19:1-19:21 (2018) - [c15]Drahomira Herrmannova, Steven Robert Young, Robert M. Patton, Christopher G. Stahl, Nicole C. Kleinstreuer, Mary S. Wolfe:
Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study. Louhi@EMNLP 2018: 71-82 - [c14]Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Neena Imam, Travis S. Humble:
Neural Networks and Graph Algorithms with Next-Generation Processors. IPDPS Workshops 2018: 1194-1203 - [c13]Adam L. Anderson, Steven R. Young, Thomas P. Karnowski, Jason M. Vann:
Deepmod: An Over-the-Air Trainable Machine Modem for Resilient PHY Layer Communications. MILCOM 2018: 213-218 - [c12]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:
167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. SC 2018: 50:1-50:11 - [i3]Drahomira Herrmannova, Steven R. Young, Robert M. Patton, Christopher G. Stahl, Nicole C. Kleinstreuer, Mary S. Wolfe:
Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study. CoRR abs/1811.01183 (2018) - 2017
- [c11]Adam M. Terwilliger, Gabriel N. Perdue, David Isele, Robert M. Patton, Steven R. Young:
Vertex reconstruction of neutrino interactions using deep learning. IJCNN 2017: 2275-2281 - [c10]Catherine D. Schuman, Thomas E. Potok, Steven R. Young, Robert M. Patton, Gabriel N. Perdue, Gangotree Chakma, Austin Wyer, Garrett S. Rose:
Neuromorphic computing for temporal scientific data classification. NCS 2017: 2:1-2:6 - [c9]J. Travis Johnston, Steven R. Young, David Hughes, Robert M. Patton, Devin White:
Optimizing Convolutional Neural Networks for Cloud Detection. MLHPC@SC 2017: 4:1-4:9 - [c8]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:
Evolving Deep Networks Using HPC. MLHPC@SC 2017: 7:1-7:7 - [i2]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:
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. CoRR abs/1703.05364 (2017) - 2016
- [c7]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:
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. MLHPC@SC 2016: 47-55 - 2015
- [j3]Junjie Lu, Steven R. Young, Itamar Arel, Jeremy Holleman:
A 1 TOPS/W Analog Deep Machine-Learning Engine With Floating-Gate Storage in 0.13 µm CMOS. IEEE J. Solid State Circuits 50(1): 270-281 (2015) - [c6]Jeremy Holleman, Itamar Arel, Steven R. Young, Junjie Lu:
Analog inference circuits for deep learning. BioCAS 2015: 1-4 - [c5]Steven R. Young, Derek C. Rose, Thomas P. Karnowski, Seung-Hwan Lim, Robert M. Patton:
Optimizing deep learning hyper-parameters through an evolutionary algorithm. MLHPC@SC 2015: 4:1-4:5 - 2014
- [j2]Steven R. Young, Andrew S. Davis, Aaron Mishtal, Itamar Arel:
Hierarchical spatiotemporal feature extraction using recurrent online clustering. Pattern Recognit. Lett. 37: 115-123 (2014) - [j1]Steven R. Young, Junjie Lu, Jeremy Holleman, Itamar Arel:
On the Impact of Approximate Computation in an Analog DeSTIN Architecture. IEEE Trans. Neural Networks Learn. Syst. 25(5): 934-946 (2014) - [c4]Junjie Lu, Steven R. Young, Itamar Arel, Jeremy Holleman:
30.10 A 1TOPS/W analog deep machine-learning engine with floating-gate storage in 0.13μm CMOS. ISSCC 2014: 504-505 - 2013
- [i1]Steven Robert Young, Itamar Arel:
Recurrent Online Clustering as a Spatio-Temporal Feature Extractor in DeSTIN. CoRR abs/1301.3385 (2013) - 2012
- [c3]Steven Robert Young, Itamar Arel:
Recurrent Clustering for Unsupervised Feature Extraction with Application to Sequence Detection. ICMLA (2) 2012: 54-55 - 2011
- [c2]Thomas P. Karnowski, Itamar Arel, Steven R. Young:
Modeling Temporal Dynamics with Function Approximation in Deep Spatio-Temporal Inference Network. BICA 2011: 174-179 - 2010
- [c1]Steven R. Young, Itamar Arel, Thomas P. Karnowski, Derek C. Rose:
A Fast and Stable Incremental Clustering Algorithm. ITNG 2010: 204-209
Coauthor Index
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