Search Results - Scott, Clayton D.

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  1. 1
    The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

    The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity by Fjeldsted, Aaron P., Morrow, Tyler J., Scott, Clayton D., Zhu, Yilun, Holland, Darren E., Lintereur, Azaree T., Wolfe, Douglas E.

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  2. 2
    AN OPERATOR THEORETIC APPROACH TO NONPARAMETRIC MIXTURE MODELS

    AN OPERATOR THEORETIC APPROACH TO NONPARAMETRIC MIXTURE MODELS by Vandermeulen, Robert A., Scott, Clayton D.

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  3. 3
    Asymptotic Source Detection Performance of Gamma-Ray Imaging Systems Under Model Mismatch

    Asymptotic Source Detection Performance of Gamma-Ray Imaging Systems Under Model Mismatch by Lingenfelter, D. J., Fessler, J. A., Scott, C. D., Zhong He

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  4. 4
    Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification

    Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification by Davenport, M A, Baraniuk, R G, Scott, C D

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  5. 5
    Scalable fused Lasso SVM for connectome-based disease prediction

    Scalable fused Lasso SVM for connectome-based disease prediction by Watanabe, Takanori, Scott, Clayton D., Kessler, Daniel, Angstadt, Michael, Sripada, ChandraS

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  6. 6
    Benefits of Position-Sensitive Detectors for Radioactive Source Detection

    Benefits of Position-Sensitive Detectors for Radioactive Source Detection by Lingenfelter, Daniel J, Fessler, Jeffrey A, Scott, Clayton D, Zhong He

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  7. 7
    Influence of Machine Learning and Gamma-Ray Spectral Parameters on Novelty Detection and Novelty Localization

    Influence of Machine Learning and Gamma-Ray Spectral Parameters on Novelty Detection and Novelty Localization by Fjeldsted, Aaron P., Holland, Darren E., Landon, George V., Scott, Clayton D., Zhu, Yilun, Lintereur, Azaree T.

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  8. 8
    L₂ Kernel Classification

    L₂ Kernel Classification by JooSeuk Kim, Scott, C

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  9. 9
    Source Detection Performance Prediction for a CdZnTe Array

    Source Detection Performance Prediction for a CdZnTe Array by Lingenfelter, D. J., Fessler, J. A., Scott, C. D., Zhong He

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  10. 10
    The One Class Support Vector Machine Solution Path

    The One Class Support Vector Machine Solution Path by Gyemin Lee, Scott, C. D.

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  11. 11
    On Classification-Calibration of Gamma-Phi Losses

    On Classification-Calibration of Gamma-Phi Losses by Wang, Yutong, Scott, Clayton D

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  12. 12
    Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel

    Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel by Wang, Yutong, Scott, Clayton D

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  13. 13
    VC dimension of partially quantized neural networks in the overparametrized regime

    VC dimension of partially quantized neural networks in the overparametrized regime by Wang, Yutong, Scott, Clayton D

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  14. 14
    An Exact Solver for the Weston-Watkins SVM Subproblem

    An Exact Solver for the Weston-Watkins SVM Subproblem by Wang, Yutong, Scott, Clayton D

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  15. 15
    On The Identifiability of Mixture Models from Grouped Samples

    On The Identifiability of Mixture Models from Grouped Samples by Vandermeulen, Robert A, Scott, Clayton D

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  16. 16
    Weston-Watkins Hinge Loss and Ordered Partitions

    Weston-Watkins Hinge Loss and Ordered Partitions by Wang, Yutong, Scott, Clayton D

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  17. 17
    Detection performance prediction for CdZnTe array

    Detection performance prediction for CdZnTe array by Lingenfelter, D. J., Fessler, J. A., Scott, C. D., Zhong He

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  18. 18
    Predicting ROC curves for source detection under model mismatch

    Predicting ROC curves for source detection under model mismatch by Lingenfelter, D J, Fessler, J A, Scott, C D, Zhong He

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  19. 19
    Learning Minimum Volume Sets with Support Vector Machines

    Learning Minimum Volume Sets with Support Vector Machines by Davenport, M.A., Baraniuk, R.G., Scott, C.D.

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  20. 20
    Benefits of position-sensitive detectors for source detection with known background

    Benefits of position-sensitive detectors for source detection with known background by Lingenfelter, D.J., Fessler, J.A., Scott, C.D., Zhong He

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