Brendon K. Colbert's Home Page

Software

Tessellated Kernel Learning

Journal Articles

B. Colbert and M. Peet

A 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.

Conference Articles

B. Colbert, L. Crespo and M. Peet

A Convex Optimization Approach to Improving Suboptimal Hyperparameters of Sliced Normal Distributions.

American Control Conference, 2020.

B. Colbert and M. Peet

Using SDP to Parameterize Universal Kernel Functions.

IEEE Conference on Decision and Control, 2019.

B. Colbert, L. Crespo and M. Peet

A Sum of Squares Optimization Approach to Uncertainty Quantification.

American Control Conference, 2019.

B. Colbert and M. Peet

Using Trajectory Measurements to Estimate the Region of Attraction of Nonlinear Systems.

IEEE Conference on Decision and Control, 2018.

B. Colbert, H. Mohammadi and M. Peet

Combining SOS with Branch and Bound to Isolate Global Solutions of Polynomial Optimization Problems.

American Control Conference, 2018.