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| Publication | Type | Year |
|---|---|---|
Machines Learning about Machines ? ML for Analysis & Control of HPC InfrastructureConference on Data Analysis (CoDA) 2020
|
Abstract – 2020 Abstract | 2020 |
RAPDARTS: Resource-Aware Progressive Differentiable Architecture SearcharXiv |
Conference Paper – 2019 Conference Paper | 2019 |
Neural Inspired Computation Remote Sensing Platform |
SAND Report – 2019 SAND Report | 2019 |
Hardware-Aware Neural Architecture SearchAgile RTL |
Presentation (non-conference) – 2019 Presentation (non-conference) | 2019 |
Machine Learning for System Software ? Can Computers Manage Computers?Sandia Machine Learning Deep Learning |
Presentation (non-conference) – 2019 Presentation (non-conference) | 2019 |
State Representation Learning for Deep PlanningSandia Machine Learning and Deep Learning Workshop 2019 |
Conference Paper – 2019 Conference Paper | 2019 |
State Representation Learning for Deep PlanningSandia Machine Learning and Deep Learning Workshop 2019 |
Conference Paper – 2019 Conference Paper | 2019 |
Benchmarking Event-Driven Neuromorphic ArchitecturesInternational Conference of Neuromorphic Systems (ICONS) 2019
|
Conference Paper – 2019 Conference Paper | 2019 |
Benchmarking Event-Driven Neuromorphic ArchitecturesInternational Conference on Neuromorphic Systems |
Conference Paper – 2019 Conference Paper | 2019 |
Neuromorphic Computing: Memristors Learn to PlayNature Electronics |
Journal Article – 2019 Journal Article | 2019 |
Distillation Strategies for Proximal Policy OptimizationIEEE Transactions on Computers
|
Journal Article – 2019 Journal Article | 2019 |
Distillation Strategies for Proximal Policy OptimizationarXiv.org
|
Journal Article – 2019 Journal Article | 2019 |
Methods for efficient deep reinforcement learningSam Green PhD proposal |
Presentation (non-conference) – 2019 Presentation (non-conference) | 2019 |
Learned P-States for High Performance ComputingPosters on the Patio |
Conference Paper – 2018 Conference Paper | 2018 |
Impacts of Mathematical Optimization on Reinforcement LearningIBM, Almaden Research Center (E3-442) |
Presentation (non-conference) – 2018 Presentation (non-conference) | 2018 |
Introduction to Neural-Inspired Computing & Impacts for SpaceSPACE COMPUTING & CONNECTED ENTERPRISE RESILIENCY CONFERENCE 2018 |
Conference Paper – 2018 Conference Paper | 2018 |
Mathematical Optimizations for Deep LearningCyber-Physical Systems and Security |
Book – 2018 Book | 2018 |
Impacts of Mathematical Optimizations on Reinforcement Learning Policy PerformanceIjcnn |
Conference Paper – 2018 Conference Paper | 2018 |
Reinforcement Learning Policy Performance Impacts of Pruning, Quantization, and CompressionNice 2018 |
Conference Paper – 2018 Conference Paper | 2018 |
Impacts of Mathematical Optimizations on Reinforcement Learning Policy PerformanceIjcnn |
Conference Paper – 2018 Conference Paper | 2018 |
Reinforcement Learning is Needed for Extreme Heterogeneity in SupercomputingThe Extreme Heterogeneity Workshop
|
Abstract – 2017 Abstract | 2017 |
Impacts of Quantization and Compression on Reinforcement Learning Policy PerformanceNICE 2018Neuro-Inspired Computational Elements Workshop
|
Abstract – 2017 Abstract | 2017 |
| Document Title | Type | Year |