Clayton D. Scott

Publication Activity (10 Years)

Years Active: 2000-2023
Publications (10 Years): 10

Top Topics

Support Vector Machine

Kernel Density Estimators

Principal Component Analysis

Top Venues

IEEE Trans. Medical Imaging

Publications

Yutong Wang, Clayton D. Scott
On Classification-Calibration of Gamma-Phi Losses. CoRR (2023)
Yutong Wang, Clayton D. Scott
Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel. CoRR (2022)
Yutong Wang, Clayton D. Scott
An exact solver for the Weston-Watkins SVM subproblem. CoRR (2021)
Yutong Wang, Clayton D. Scott
VC dimension of partially quantized neural networks in the overparametrized regime. CoRR (2021)
Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. NeurIPS (2020)
Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. CoRR (2020)
Yutong Wang, Clayton D. Scott
Weston-Watkins Hinge Loss and Ordered Partitions. CoRR (2020)
Alexander Ritchie, Laura Balzano, Clayton D. Scott
Supervised PCA: A Multiobjective Approach. CoRR (2020)
Alexander Ritchie, Clayton D. Scott, Laura Balzano, Daniel Kessler, Chandra Sekhar Sripada
Supervised Principal Component Analysis Via Manifold Optimization. DSW (2019)
Gopal Nataraj, Jon-Fredrik Nielsen, Clayton D. Scott, Jeffrey A. Fessler
Dictionary-Free MRI PERK: Parameter Estimation via Regression with Kernels. IEEE Trans. Medical Imaging 37 (9) (2018)
Robert A. Vandermeulen, Clayton D. Scott
On The Identifiability of Mixture Models from Grouped Samples. CoRR (2015)
Takanori Watanabe, Daniel Kessler, Clayton D. Scott, Michael Angstadt, Chandra Sekhar Sripada
Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine. NeuroImage 96 (2014)
Robert A. Vandermeulen, Clayton D. Scott
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space. NIPS (2014)
Takanori Watanabe, Clayton D. Scott, Daniel Kessler, Michael Angstadt, Chandra Sekhar Sripada
Scalable fused Lasso SVM for connectome-based disease prediction. ICASSP (2014)
Chandra Sekhar Sripada, Daniel Kessler, Robert C. Welsh, Michael Angstadt, Israel Liberzon, K. Luan Phan, Clayton D. Scott
Distributed effects of methylphenidate on the network structure of the resting brain: A connectomic pattern classification analysis. NeuroImage 81 (2013)
Robert A. Vandermeulen, Clayton D. Scott
Consistency of Robust Kernel Density Estimators. COLT (2013)
Takanori Watanabe, Clayton D. Scott
Spatial Confidence Regions for Quantifying and Visualizing Registration Uncertainty. WBIR (2012)
JooSeuk Kim, Clayton D. Scott
Robust kernel density estimation. J. Mach. Learn. Res. 13 (2012)
Daniel J. Lingenfelter, Jeffrey A. Fessler, Clayton D. Scott, Zhong He
Asymptotic Source Detection Performance of Gamma-Ray Imaging Systems Under Model Mismatch. IEEE Trans. Signal Process. 59 (11) (2011)
JooSeuk Kim, Clayton D. Scott
Robust Kernel Density Estimation CoRR (2011)
JooSeuk Kim, Clayton D. Scott
On the Robustness of Kernel Density M-Estimators. ICML (2011)
Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification. IEEE Trans. Pattern Anal. Mach. Intell. 32 (10) (2010)
JooSeuk Kim, Clayton D. Scott
Kernel Classification. IEEE Trans. Pattern Anal. Mach. Intell. 32 (10) (2010)
Daniel J. Lingenfelter, Jeffrey A. Fessler, Clayton D. Scott, Zhong He
Benefits of position-sensitive detectors for radioactive source detection. IEEE Trans. Signal Process. 58 (9) (2010)
Frederic Thouin, Mark Coates, Brian Eriksson, Robert D. Nowak, Clayton D. Scott
Learning to satisfy. ICASSP (2008)
JooSeuk Kim, Clayton D. Scott
Performance analysis for L_2 kernel classification. NIPS (2008)
Aarti Singh, Robert D. Nowak, Clayton D. Scott
Adaptive Hausdorff Estimation of Density Level Sets. COLT (2008)
Parminder Chhabra, Clayton D. Scott, Eric D. Kolaczyk, Mark Crovella
Distributed Spatial Anomaly Detection. INFOCOM (2008)
JooSeuk Kim, Clayton D. Scott
Robust kernel density estimation. ICASSP (2008)
Clayton D. Scott, Mark A. Davenport
Regression Level Set Estimation Via Cost-Sensitive Classification. IEEE Trans. Signal Process. 55 (6-1) (2007)
Clayton D. Scott, Robert D. Nowak
Learning Minimum Volume Sets. J. Mach. Learn. Res. 7 (2006)
Clayton D. Scott, Robert D. Nowak
Robust Contour Matching Via the Order-Preserving Assignment Problem. IEEE Trans. Image Process. 15 (7) (2006)
Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
Controlling False Alarms With Support Vector Machines. ICASSP (5) (2006)
Clayton D. Scott, Robert D. Nowak
Minimax-optimal classification with dyadic decision trees. IEEE Trans. Inf. Theory 52 (4) (2006)
Clayton D. Scott, Robert D. Nowak
A Neyman-Pearson approach to statistical learning. IEEE Trans. Inf. Theory 51 (11) (2005)
Clayton D. Scott, Robert D. Nowak
Learning Minimum Volume Sets. NIPS (2005)
Clayton D. Scott, Robert D. Nowak
On the Adaptive Properties of Decision Trees. NIPS (2004)
Clayton D. Scott, Robert D. Nowak
TEMPLAR: a wavelet-based framework for pattern learning and analysis. IEEE Trans. Signal Process. 52 (8) (2004)
Clayton D. Scott, Rebecca M. Willett, Robert D. Nowak
CORT: classification or regression trees. ICASSP (6) (2003)
Clayton D. Scott, Robert D. Nowak
Near-Minimax Optimal Classification with Dyadic Classification Trees. NIPS (2003)
Clayton D. Scott, Robert D. Nowak
Dyadic Classification Trees via Structural Risk Minimization. NIPS (2002)
Clayton D. Scott, Robert D. Nowak
A Novel Hierarchical Wavelet-Based Framework for Pattern Analysis and Synthesis. SSIAI (2000)
Clayton D. Scott, Robert D. Nowak
Pattern Extraction and Synthesis Using a Hierarchical Wavelet-Based Framework. ICIP (2000)