Michael R. Smith

42 papers B 5C 5Journal 23Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	C	`conf`	From Uncertainty to Clarity: Projecting Points onto Classification Boundaries Using Distance Metrics. ICMLA Michael R. Smith, Eva Domschot
2025	J	`jnl`	Surveying the Operational Cybersecurity and Supply Chain Threat Landscape when Developing and Deploying AI Systems. CoRR Michael R. Smith, Joe Ingram
2025	C	`conf`	Topology of Out-of-Distribution Examples in Deep Neural Networks. ICMLA Esha Datta, Johanna Hennig, Eva Domschot, Connor Mattes, Michael R. Smith
2025	J	`jnl`	Topology of Out-of-Distribution Examples in Deep Neural Networks. CoRR Esha Datta, Johanna Hennig, Eva Domschot, Connor Mattes, Michael R. Smith
2024	—	`conf`	Anomaly Detection in Video Using Compression. MIPR Michael R. Smith, Renee Gooding, Jonathan Bisila, Christina L. Ting
2024	J	`jnl`	Improving Automated Labeling for ATT&CK Tactics in Malware Threat Reports. DTRAP Eva Domschot, Ramyaa Ramyaa, Michael R. Smith
2023	—	`conf`	Assessing the Fidelity of Explanations with Global Sensitivity Analysis. HICSS Michael R. Smith, Erin Acquesta, Charles Smutz, Ahmad Rushdi, Blake Moss
2021	—	`conf`	Malware Generation with Specific Behaviors to Improve Machine Learning-based Detection. IEEE BigData Michael R. Smith, Stephen J. Verzi, Nicholas T. Johnson, Xin Zhou, Kanad Khanna, Sophie Quynn, Raga Krishnakumar
2021	—	`conf`	Sage Advice? The Impacts of Explanations for Machine Learning Models on Human Decision-Making in Spam Detection. HCI (36) Mallory C. Stites, Megan Nyre-Yu, Blake Moss, Charles Smutz, Michael R. Smith
2020	J	`jnl`	Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence. Frontiers Comput. Neurosci. Frances S. Chance, James B. Aimone, Srideep Musuvathy, Michael R. Smith, Craig M. Vineyard, Felix Wang
2020	J	`jnl`	Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security. CoRR 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
2020	—	`conf`	Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Malware Analysis. AISec@CCS 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
2020	J	`jnl`	Self-Updating Models with Error Remediation. CoRR Justin E. Doak, Michael R. Smith, Joey B. Ingram
2018	C	`conf`	Dynamic Analysis of Executables to Detect and Characterize Malware. ICMLA Michael R. Smith, Joe Ingram, Christopher C. Lamb, Timothy Draelos, Justin E. Doak, James B. Aimone, Conrad D. James
2018	J	`jnl`	The robustness of majority voting compared to filtering misclassified instances in supervised classification tasks. Artif. Intell. Rev. Michael R. Smith, Tony R. Martinez
2017	J	`jnl`	A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines. CoRR 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
2017	—	`conf`	A Spike-Timing Neuromorphic Architecture. ICRC 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
2017	B	`conf`	A novel digital neuromorphic architecture efficiently facilitating complex synaptic response functions applied to liquid state machines. IJCNN 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
2017	J	`jnl`	Dynamic Analysis of Executables to Detect and Characterize Malware. CoRR Michael R. Smith, Joe B. Ingram, Christopher C. Lamb, Timothy J. Draelos, Justin E. Doak, James B. Aimone, Conrad D. James
2016	J	`jnl`	A Comparative Evaluation of Curriculum Learning with Filtering and Boosting in Supervised Classification Problems. Comput. Intell. Michael R. Smith, Tony R. Martinez
2016	J	`jnl`	Missing Value Imputation with Unsupervised Backpropagation. Comput. Intell. Michael S. Gashler, Michael R. Smith, Richard G. Morris, Tony R. Martinez
2015	J	`jnl`	A Minimal Architecture for General Cognition. CoRR Michael S. Gashler, Zachariah Kindle, Michael R. Smith
2015	B	`conf`	A hybrid latent variable neural network model for item recommendation. IJCNN Michael R. Smith, Michael S. Gashler, Tony R. Martinez
2015	B	`conf`	A minimal architecture for general cognition. IJCNN Michael S. Gashler, Zachariah Kindle, Michael R. Smith
2015	—	`conf`	The Potential Benefits of Data Set Filtering and Learning Algorithm Hyperparameter Optimization. MetaSel@PKDD/ECML Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier
2015	B	`conf`	Using Classifier diversity to handle label noise. IJCNN Michael R. Smith, Tony R. Martinez
2014	J	`jnl`	A Hierarchical Multi-Output Nearest Neighbor Model for Multi-Output Dependence Learning. CoRR Richard G. Morris, Tony R. Martinez, Michael R. Smith
2014	J	`jnl`	A Hybrid Latent Variable Neural Network Model for Item Recommendation. CoRR Michael R. Smith, Tony R. Martinez, Michael Gashler
2014	—	`conf`	An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. MetaSel@ECAI Michael R. Smith, Andrew White, Christophe G. Giraud-Carrier, Tony R. Martinez
2014	J	`jnl`	An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. CoRR Michael R. Smith, Andrew White, Christophe G. Giraud-Carrier, Tony R. Martinez
2014	J	`jnl`	An instance level analysis of data complexity. Mach. Learn. Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier
2014	J	`jnl`	Becoming More Robust to Label Noise with Classifier Diversity. CoRR Michael R. Smith, Tony R. Martinez
2014	C	`conf`	Nehovah: A Neologism Creator Nomen Ipsum. ICCC Michael R. Smith, Ryan S. Hintze, Dan Ventura
2014	—	`conf`	Recommending Learning Algorithms and Their Associated Hyperparameters. MetaSel@ECAI Michael R. Smith, Logan Mitchell, Christophe G. Giraud-Carrier, Tony R. Martinez
2014	J	`jnl`	Recommending Learning Algorithms and Their Associated Hyperparameters. CoRR Michael R. Smith, Logan Mitchell, Christophe G. Giraud-Carrier, Tony R. Martinez
2014	C	`conf`	Reducing the Effects of Detrimental Instances. ICMLA Michael R. Smith, Tony R. Martinez
2014	J	`jnl`	Reducing the Effects of Detrimental Instances. CoRR Michael R. Smith, Tony R. Martinez
2014	J	`jnl`	The Potential Benefits of Filtering Versus Hyper-Parameter Optimization. CoRR Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier
2013	J	`jnl`	A Comparative Evaluation of Curriculum Learning with Filtering and Boosting. CoRR Michael R. Smith, Tony R. Martinez
2013	J	`jnl`	An Extensive Evaluation of Filtering Misclassified Instances in Supervised Classification Tasks. CoRR Michael R. Smith, Tony R. Martinez
2013	J	`jnl`	Missing Value Imputation With Unsupervised Backpropagation. CoRR Michael Gashler, Michael R. Smith, Richard G. Morris, Tony R. Martinez
2011	B	`conf`	Improving classification accuracy by identifying and removing instances that should be misclassified. IJCNN Michael R. Smith, Tony R. Martinez