Michael R. Smith

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 15

Top Topics

Top Venues

Comput. Intell.

Publications

Michael R. Smith, Erin Acquesta, Charles Smutz, Ahmad Rushdi, Blake Moss
Assessing the Fidelity of Explanations with Global Sensitivity Analysis. HICSS (2023)
Mallory C. Stites, Megan Nyre-Yu, Blake Moss, Charles Smutz, Michael R. Smith
Sage Advice? The Impacts of Explanations for Machine Learning Models on Human Decision-Making in Spam Detection. HCI (36) (2021)
Michael R. Smith, Stephen J. Verzi, Nicholas T. Johnson, Xin Zhou, Kanad Khanna, Sophie Quynn, Raga Krishnakumar
Malware Generation with Specific Behaviors to Improve Machine Learning-based Detection. IEEE BigData (2021)
Michael R. Smith, Nicholas T. Johnson, Joe B. Ingram, Armida J. Carbajal, Bridget I. Haus, Eva Domschot, Ramyaa, Christopher C. Lamb, Stephen J. Verzi, W. Philip Kegelmeyer
Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Malware Analysis. AISec@CCS (2020)
Frances S. Chance, James B. Aimone, Srideep Musuvathy, Michael R. Smith, Craig M. Vineyard, Felix Wang
Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence. Frontiers Comput. Neurosci. 14 (2020)
Justin E. Doak, Michael R. Smith, Joey B. Ingram
Self-Updating Models with Error Remediation. CoRR (2020)
Michael R. Smith, Nicholas T. Johnson, Joe B. Ingram, Armida J. Carbajal, Ramyaa Ramyaa, Evelyn Domschot, Christopher C. Lamb, Stephen J. Verzi, W. Philip Kegelmeyer
Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security. CoRR (2020)
Michael R. Smith, Tony R. Martinez
The robustness of majority voting compared to filtering misclassified instances in supervised classification tasks. Artif. Intell. Rev. 49 (1) (2018)
Michael R. Smith, Joe Ingram, Christopher C. Lamb, Timothy Draelos, Justin E. Doak, James B. Aimone, Conrad D. James
Dynamic Analysis of Executables to Detect and Characterize Malware. ICMLA (2018)
Aaron J. Hill, Jonathon W. Donaldson, Fredrick H. Rothganger, Craig M. Vineyard, David R. Follett, Pamela L. Follett, Michael R. Smith, Stephen J. Verzi, William Severa, Felix Wang, James B. Aimone, John H. Naegle, Conrad D. James
A Spike-Timing Neuromorphic Architecture. ICRC (2017)
Michael R. Smith, Joe B. Ingram, Christopher C. Lamb, Timothy J. Draelos, Justin E. Doak, James B. Aimone, Conrad D. James
Dynamic Analysis of Executables to Detect and Characterize Malware. CoRR (2017)
Michael R. Smith, Aaron J. Hill, Kristofor D. Carlson, Craig M. Vineyard, Jonathon Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James B. Aimone
A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines. CoRR (2017)
Michael R. Smith, Aaron J. Hill, Kristofor D. Carlson, Craig M. Vineyard, Jonathon Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James B. Aimone
A novel digital neuromorphic architecture efficiently facilitating complex synaptic response functions applied to liquid state machines. IJCNN (2017)
Michael S. Gashler, Michael R. Smith, Richard G. Morris, Tony R. Martinez
Missing Value Imputation with Unsupervised Backpropagation. Comput. Intell. 32 (2) (2016)
Michael R. Smith, Tony R. Martinez
A Comparative Evaluation of Curriculum Learning with Filtering and Boosting in Supervised Classification Problems. Comput. Intell. 32 (2) (2016)
Michael R. Smith, Tony R. Martinez
Using Classifier diversity to handle label noise. IJCNN (2015)
Michael S. Gashler, Zachariah Kindle, Michael R. Smith
A minimal architecture for general cognition. IJCNN (2015)
Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier
The Potential Benefits of Data Set Filtering and Learning Algorithm Hyperparameter Optimization. MetaSel@PKDD/ECML (2015)
Michael R. Smith, Michael S. Gashler, Tony R. Martinez
A hybrid latent variable neural network model for item recommendation. IJCNN (2015)
Michael S. Gashler, Zachariah Kindle, Michael R. Smith
A Minimal Architecture for General Cognition. CoRR (2015)
Michael R. Smith, Logan Mitchell, Christophe G. Giraud-Carrier, Tony R. Martinez
Recommending Learning Algorithms and Their Associated Hyperparameters. MetaSel@ECAI (2014)
Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier
The Potential Benefits of Filtering Versus Hyper-Parameter Optimization. CoRR (2014)
Michael R. Smith, Tony R. Martinez
Becoming More Robust to Label Noise with Classifier Diversity. CoRR (2014)
Michael R. Smith, Andrew White, Christophe G. Giraud-Carrier, Tony R. Martinez
An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. MetaSel@ECAI (2014)
Michael R. Smith, Ryan S. Hintze, Dan Ventura
Nehovah: A Neologism Creator Nomen Ipsum. ICCC (2014)
Michael R. Smith, Tony R. Martinez, Michael Gashler
A Hybrid Latent Variable Neural Network Model for Item Recommendation. CoRR (2014)
Richard G. Morris, Tony R. Martinez, Michael R. Smith
A Hierarchical Multi-Output Nearest Neighbor Model for Multi-Output Dependence Learning. CoRR (2014)
Michael R. Smith, Andrew White, Christophe G. Giraud-Carrier, Tony R. Martinez
An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. CoRR (2014)
Michael R. Smith, Logan Mitchell, Christophe G. Giraud-Carrier, Tony R. Martinez
Recommending Learning Algorithms and Their Associated Hyperparameters. CoRR (2014)
Michael R. Smith, Tony R. Martinez
Reducing the Effects of Detrimental Instances. CoRR (2014)
Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier
An instance level analysis of data complexity. Mach. Learn. 95 (2) (2014)
Michael R. Smith, Tony R. Martinez
Reducing the Effects of Detrimental Instances. ICMLA (2014)
Michael Gashler, Michael R. Smith, Richard G. Morris, Tony R. Martinez
Missing Value Imputation With Unsupervised Backpropagation. CoRR (2013)
Michael R. Smith, Tony R. Martinez
A Comparative Evaluation of Curriculum Learning with Filtering and Boosting. CoRR (2013)
Michael R. Smith, Tony R. Martinez
An Extensive Evaluation of Filtering Misclassified Instances in Supervised Classification Tasks. CoRR (2013)
Michael R. Smith, Tony R. Martinez
Improving classification accuracy by identifying and removing instances that should be misclassified. IJCNN (2011)