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2020 – today
- 2022
[j16]Hamed Hamze Bajgiran
, Pau Batlle, Houman Owhadi, Mostafa Samir, Clint Scovel, Mahdy Shirdel, Michael Stanley, Peyman Tavallali:
Uncertainty quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball. J. Comput. Phys. 471: 111608 (2022)- 2021
- [i6]Hamed Hamze Bajgiran, Pau Batlle Franch, Houman Owhadi, Clint Scovel, Mahdy Shirdel, Michael Stanley, Peyman Tavallali:
Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball. CoRR abs/2108.10517 (2021)
2010 – 2019
- 2019
- [i5]Houman Owhadi, Clint Scovel, Gene Ryan Yoo:
Kernel Mode Decomposition and programmable/interpretable regression networks. CoRR abs/1907.08592 (2019) - 2015
- [j15]Houman Owhadi, Clint Scovel, Timothy John Sullivan:
On the Brittleness of Bayesian Inference. SIAM Rev. 57(4): 566-582 (2015) - [i4]Houman Owhadi, Clint Scovel:
Machine Wald. CoRR abs/1508.02449 (2015) - 2013
- [j14]Houman Owhadi, Clint Scovel, Timothy John Sullivan, Mike McKerns, Michael Ortiz:
Optimal Uncertainty Quantification. SIAM Rev. 55(2): 271-345 (2013) - 2012
- [i3]Mike McKerns, Houman Owhadi, Clint Scovel, Timothy John Sullivan, Michael Ortiz:
The Optimal Uncertainty Algorithm in the Mystic Framework. CoRR abs/1202.1055 (2012) - 2011
- [j13]Ingo Steinwart, Don R. Hush, Clint Scovel:
Training SVMs Without Offset. J. Mach. Learn. Res. 12: 141-202 (2011) - 2010
- [j12]Clint Scovel, Don R. Hush, Ingo Steinwart, James Theiler:
Radial kernels and their reproducing kernel Hilbert spaces. J. Complex. 26(6): 641-660 (2010) - [j11]James Theiler, Clint Scovel, Brendt Wohlberg, Bernard R. Foy:
Elliptically Contoured Distributions for Anomalous Change Detection in Hyperspectral Imagery. IEEE Geosci. Remote. Sens. Lett. 7(2): 271-275 (2010) - [i2]Houman Owhadi, Clint Scovel, Timothy John Sullivan, Mike McKerns, Michael Ortiz:
Optimal Uncertainty Quantification. CoRR abs/1009.0679 (2010)
2000 – 2009
- 2009
- [j10]Ingo Steinwart, Don R. Hush, Clint Scovel:
Learning from dependent observations. J. Multivar. Anal. 100(1): 175-194 (2009) - [c9]James Theiler, Clint Scovel:
Uncorrelated versus independent elliptically-contoured distributions for anomalous change detection in hyperspectral imagery. Computational Imaging 2009: 72460 - [c8]Ingo Steinwart, Don R. Hush, Clint Scovel:
Optimal Rates for Regularized Least Squares Regression. COLT 2009 - 2007
- [j9]Don R. Hush, Clint Scovel, Ingo Steinwart:
Stability of Unstable Learning Algorithms. Mach. Learn. 67(3): 197-206 (2007) - [c7]Nikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart:
Gaps in Support Vector Optimization. COLT 2007: 336-348 - 2006
- [j8]Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart:
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines. J. Mach. Learn. Res. 7: 733-769 (2006) - [j7]Ingo Steinwart, Don R. Hush, Clint Scovel:
An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels. IEEE Trans. Inf. Theory 52(10): 4635-4643 (2006) - [c6]Ingo Steinwart, Don R. Hush, Clint Scovel:
Function Classes That Approximate the Bayes Risk. COLT 2006: 79-93 - [c5]Ingo Steinwart, Don R. Hush, Clint Scovel:
An Oracle Inequality for Clipped Regularized Risk Minimizers. NIPS 2006: 1321-1328 - 2005
- [j6]Ingo Steinwart, Don R. Hush, Clint Scovel:
A Classification Framework for Anomaly Detection. J. Mach. Learn. Res. 6: 211-232 (2005) - [c4]Ingo Steinwart, Clint Scovel:
Fast Rates for Support Vector Machines. COLT 2005: 279-294 - 2004
- [j5]Don R. Hush, Clint Scovel:
Fat-Shattering of Affine Functions. Comb. Probab. Comput. 13(3): 353-360 (2004) - [c3]Ingo Steinwart, Don R. Hush, Clint Scovel:
Density Level Detection is Classification. NIPS 2004: 1337-1344 - [c2]Ingo Steinwart, Clint Scovel:
Fast Rates to Bayes for Kernel Machines. NIPS 2004: 1345-1352 - 2003
- [j4]Don R. Hush, Clint Scovel:
Polynomial-Time Decomposition Algorithms for Support Vector Machines. Mach. Learn. 51(1): 51-71 (2003) - [j3]Mike Cannon, Mike Fugate, Don R. Hush, Clint Scovel:
Selecting a restoration technique to minimize OCR error. IEEE Trans. Neural Networks 14(3): 478-490 (2003) - 2002
- [j2]Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint Scovel:
Machine Learning with Data Dependent Hypothesis Classes. J. Mach. Learn. Res. 2: 335-358 (2002) - 2001
- [j1]Don R. Hush, Clint Scovel:
On the VC Dimension of Bounded Margin Classifiers. Mach. Learn. 45(1): 33-44 (2001)
1990 – 1999
- 1998
- [c1]Judith Hochberg, Clint Scovel, Timothy Thomas, Sam Hall:
Bayesian Stratified Sampling to Assess Corpus Utility. VLC@COLING/ACL 1998 - [i1]Judith Hochberg, Clint Scovel, Timothy Thomas, Sam Hall:
Bayesian Stratified Sampling to Assess Corpus Utility. CoRR cmp-lg/9806012 (1998)
Coauthor Index
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