Michael R. Smith
Orcid: 0000-0002-2279-9701Affiliations:
- Sandia National Laboratories, Albuquerque, NM, USA
- Brigham Young University, Provo, UT, USA (former)
According to our database1,
Michael R. Smith
authored at least 31 papers
between 2011 and 2024.
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Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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Bibliography
2024
DTRAP, 2024
Proceedings of the 7th IEEE International Conference on Multimedia Information Processing and Retrieval, 2024
2023
Proceedings of the 56th Hawaii International Conference on System Sciences, 2023
2021
Sage Advice? The Impacts of Explanations for Machine Learning Models on Human Decision-Making in Spam Detection.
Proceedings of the Artificial Intelligence in HCI, 2021
Malware Generation with Specific Behaviors to Improve Machine Learning-based Detection.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021
2020
Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence.
Frontiers Comput. Neurosci., 2020
Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security.
CoRR, 2020
Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Malware Analysis.
Proceedings of the AISec@CCS 2020: Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security, 2020
2018
The robustness of majority voting compared to filtering misclassified instances in supervised classification tasks.
Artif. Intell. Rev., 2018
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018
2017
A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines.
CoRR, 2017
A novel digital neuromorphic architecture efficiently facilitating complex synaptic response functions applied to liquid state machines.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
Proceedings of the IEEE International Conference on Rebooting Computing, 2017
2016
A Comparative Evaluation of Curriculum Learning with Filtering and Boosting in Supervised Classification Problems.
Comput. Intell., 2016
2015
The Potential Benefits of Data Set Filtering and Learning Algorithm Hyperparameter Optimization.
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
2014
A Hierarchical Multi-Output Nearest Neighbor Model for Multi-Output Dependence Learning.
CoRR, 2014
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014
Proceedings of the Fifth International Conference on Computational Creativity, 2014
An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage.
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014
2013
CoRR, 2013
An Extensive Evaluation of Filtering Misclassified Instances in Supervised Classification Tasks.
CoRR, 2013
2011
Improving classification accuracy by identifying and removing instances that should be misclassified.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011