SoftwareTessellated Kernel Learning
B. Colbert and M. PeetA Convex Parametrization of a New Class of Universal Kernel Functions for use in Kernel Learning.
Journal of Machine Learning Research. Vol. 21, No. 45, 2020.
B. Colbert, L. Crespo and M. PeetA Convex Optimization Approach to Improving Suboptimal Hyperparameters of Sliced Normal Distributions.
American Control Conference, 2020.
B. Colbert and M. PeetUsing SDP to Parameterize Universal Kernel Functions.
IEEE Conference on Decision and Control, 2019.
B. Colbert, L. Crespo and M. PeetA Sum of Squares Optimization Approach to Uncertainty Quantification.
American Control Conference, 2019.
B. Colbert and M. PeetUsing Trajectory Measurements to Estimate the Region of Attraction of Nonlinear Systems.
IEEE Conference on Decision and Control, 2018.
B. Colbert, H. Mohammadi and M. PeetCombining SOS with Branch and Bound to Isolate Global Solutions of Polynomial Optimization Problems.
American Control Conference, 2018.