Clint Scovel

According to our database, Clint Scovel authored at least 29 papers between 1998 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Uncertainty quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball.

Hamed Hamze Bajgiran, Pau Batlle, Houman Owhadi, Mostafa Samir, Clint Scovel, Mahdy Shirdel, Michael Stanley, Peyman Tavallali

J. Comput. Phys., 2022

2021

Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball.

Hamed Hamze Bajgiran, Pau Batlle Franch, Houman Owhadi, Clint Scovel, Mahdy Shirdel, Michael Stanley, Peyman Tavallali

CoRR, 2021

2019

Kernel Mode Decomposition and programmable/interpretable regression networks.

Houman Owhadi, Clint Scovel, Gene Ryan Yoo

CoRR, 2019

2015

On the Brittleness of Bayesian Inference.

Houman Owhadi, Clint Scovel, Timothy John Sullivan

SIAM Rev., 2015

Machine Wald.

Houman Owhadi, Clint Scovel

CoRR, 2015

2013

Optimal Uncertainty Quantification.

Houman Owhadi, Clint Scovel, Timothy John Sullivan, Mike McKerns, Michael Ortiz

SIAM Rev., 2013

2012

The Optimal Uncertainty Algorithm in the Mystic Framework

Mike McKerns, Houman Owhadi, Clint Scovel, Timothy John Sullivan, Michael Ortiz

CoRR, 2012

2011

Training SVMs Without Offset.

Ingo Steinwart, Don R. Hush, Clint Scovel

J. Mach. Learn. Res., 2011

2010

Elliptically Contoured Distributions for Anomalous Change Detection in Hyperspectral Imagery.

James Theiler, Clint Scovel, Brendt Wohlberg, Bernard R. Foy

IEEE Geosci. Remote. Sens. Lett., 2010

Radial kernels and their reproducing kernel Hilbert spaces.

Clint Scovel, Don R. Hush, Ingo Steinwart, James Theiler

J. Complex., 2010

2009

Learning from dependent observations.

Ingo Steinwart, Don R. Hush, Clint Scovel

J. Multivar. Anal., 2009

Optimal Rates for Regularized Least Squares Regression.

Ingo Steinwart, Don R. Hush, Clint Scovel

Proceedings of the COLT 2009, 2009

Uncorrelated versus independent elliptically-contoured distributions for anomalous change detection in hyperspectral imagery.

James Theiler, Clint Scovel

Proceedings of the Computational Imaging VII, 2009

2007

Stability of Unstable Learning Algorithms.

Don R. Hush, Clint Scovel, Ingo Steinwart

Mach. Learn., 2007

Gaps in Support Vector Optimization.

Nikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart

Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006

An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels.

Ingo Steinwart, Don R. Hush, Clint Scovel

IEEE Trans. Inf. Theory, 2006

QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines.

Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart

J. Mach. Learn. Res., 2006

An Oracle Inequality for Clipped Regularized Risk Minimizers.

Ingo Steinwart, Don R. Hush, Clint Scovel

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Function Classes That Approximate the Bayes Risk.

Ingo Steinwart, Don R. Hush, Clint Scovel

Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005

A Classification Framework for Anomaly Detection.

Ingo Steinwart, Don R. Hush, Clint Scovel

J. Mach. Learn. Res., 2005

Fast Rates for Support Vector Machines.

Ingo Steinwart, Clint Scovel

Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004

Fat-Shattering of Affine Functions.

Don R. Hush, Clint Scovel

Comb. Probab. Comput., 2004

Fast Rates to Bayes for Kernel Machines.

Ingo Steinwart, Clint Scovel

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Density Level Detection is Classification.

Ingo Steinwart, Don R. Hush, Clint Scovel

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003

Selecting a restoration technique to minimize OCR error.

Mike Cannon, Mike Fugate, Don R. Hush, Clint Scovel

IEEE Trans. Neural Networks, 2003

Polynomial-Time Decomposition Algorithms for Support Vector Machines.

Don R. Hush, Clint Scovel

Mach. Learn., 2003

2002

Machine Learning with Data Dependent Hypothesis Classes.

Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint Scovel

J. Mach. Learn. Res., 2002

2001

On the VC Dimension of Bounded Margin Classifiers.

Don R. Hush, Clint Scovel

Mach. Learn., 2001

1998

Bayesian Stratified Sampling to Assess Corpus Utility.

Judith Hochberg, Clint Scovel, Timothy Thomas, Sam Hall

Proceedings of the Sixth Workshop on Very Large Corpora, 1998