Michael S. Gashler
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Deep learning in robotics: a review of recent research
HA Pierson, MS Gashler
Advanced Robotics 31 (16), 821-835, 2017
Decision tree ensemble: Small heterogeneous is better than large homogeneous
M Gashler, C Giraud-Carrier, T Martinez
2008 Seventh International Conference on Machine Learning and Applications …, 2008
Iterative non-linear dimensionality reduction with manifold sculpting
M Gashler, D Ventura, T Martinez
Advances in Neural Information Processing Systems, 513-520, 2008
Neural decomposition of time-series data for effective generalization
LB Godfrey, MS Gashler
IEEE transactions on neural networks and learning systems 29 (7), 2973-2985, 2017
Waffles: A Machine Learning Toolkit
M Gashler
The Journal of Machine Learning Research 12, 2383-2387, 2011
Security requirement determination
S Lange, GD Fee, A Goldfeder, I Medvedev, M Gashler
US Patent 7,743,423, 2010
A Continuum among Logarithmic, Linear, and Exponential Functions, and Its Potential to Improve Generalization in Neural Networks
LB Godfrey, MS Gashler
Proceedings of the International Conference on Knowledge Discovery and …, 2015
Training Deep Fourier Neural Networks To Fit Time-Series Data
MS Gashler, SC Ashmore
Lecture Notes in Computer Science 8590 (10th International Conference, ICIC …, 2014
Modeling time series data with deep Fourier neural networks
MS Gashler, SC Ashmore
Neurocomputing 188, 3-11, 2016
Hosted code runtime protection
CW Brumme, S Lange, GD Fee, M Gashler, M Prakriya
US Patent 7,647,629, 2010
Manifold learning by graduated optimization
M Gashler, D Ventura, T Martinez
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 1–13, 2011
Temporal nonlinear dimensionality reduction
M Gashler, T Martinez
The 2011 International Joint Conference on Neural Networks, 1959-1966, 2011
Robust manifold learning with CycleCut
M Gashler, T Martinez
Connection Science 24 (1), 57-69, 2012
Missing Value Imputation With Unsupervised Backpropagation
MS Gashler, MR Smith, T Martinez, R Morris
Computational Intelligence 32 (2), page 165, 2016
Automatic clustering of sequential design behaviors
MH Rahman, M Gashler, C Xie, Z Sha
International Design Engineering Technical Conferences and Computers and …, 2018
Tangent space guided intelligent neighbor finding
M Gashler, T Martinez
The 2011 International Joint Conference on Neural Networks, 2617-2624, 2011
An investigation of how neural networks learn from the experiences of peers through periodic weight averaging
J Smith, M Gashler
2017 16th IEEE International Conference on Machine Learning and Applications …, 2017
A parameterized activation function for learning fuzzy logic operations in deep neural networks
LB Godfrey, MS Gashler
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017
A method for finding similarity between multi-layer perceptrons by Forward Bipartite Alignment
S Ashmore, M Gashler
2015 International Joint Conference on Neural Networks (IJCNN), 1-7, 2015
A Hybrid Latent Variable Neural Network Model for Item Recommendation
MR Smith, T Martinez, M Gashler
Proceedings of the IEEE 2015 International Joint Conference on Neural …, 2015
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