Clayton D. Scott

43 papers A* 5B 1Misc 3Journal 23Unranked 11
YearRankTypeTitle / Venue / Authors
2023 J jnl
On Classification-Calibration of Gamma-Phi Losses.
CoRR
Yutong Wang, Clayton D. Scott
2022 J jnl
Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel.
CoRR
Yutong Wang, Clayton D. Scott
2021 J jnl
An exact solver for the Weston-Watkins SVM subproblem.
CoRR
Yutong Wang, Clayton D. Scott
2021 J jnl
VC dimension of partially quantized neural networks in the overparametrized regime.
CoRR
Yutong Wang, Clayton D. Scott
2020 A* conf
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations.
NeurIPS
Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
2020 J jnl
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations.
CoRR
Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
2020 J jnl
Supervised PCA: A Multiobjective Approach.
CoRR
Alexander Ritchie, Laura Balzano, Clayton D. Scott
2020 J jnl
Weston-Watkins Hinge Loss and Ordered Partitions.
CoRR
Yutong Wang, Clayton D. Scott
2019 — conf
Supervised Principal Component Analysis Via Manifold Optimization.
DSW
Alexander Ritchie, Clayton D. Scott, Laura Balzano, Daniel Kessler, Chandra Sekhar Sripada
2018 J jnl
Dictionary-Free MRI PERK: Parameter Estimation via Regression with Kernels.
IEEE Trans. Medical Imaging
Gopal Nataraj, Jon-Fredrik Nielsen, Clayton D. Scott, Jeffrey A. Fessler
2015 J jnl
On The Identifiability of Mixture Models from Grouped Samples.
CoRR
Robert A. Vandermeulen, Clayton D. Scott
2014 J jnl
Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine.
NeuroImage
Takanori Watanabe, Daniel Kessler, Clayton D. Scott, Michael Angstadt, Chandra Sekhar Sripada
2014 — conf
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space.
NIPS
Robert A. Vandermeulen, Clayton D. Scott
2014 Misc conf
Scalable fused Lasso SVM for connectome-based disease prediction.
ICASSP
Takanori Watanabe, Clayton D. Scott, Daniel Kessler, Michael Angstadt, Chandra Sekhar Sripada
2013 A* conf
Consistency of Robust Kernel Density Estimators.
COLT
Robert A. Vandermeulen, Clayton D. Scott
2013 J jnl
Distributed effects of methylphenidate on the network structure of the resting brain: A connectomic pattern classification analysis.
NeuroImage
Chandra Sekhar Sripada, Daniel Kessler, Robert C. Welsh, Michael Angstadt, Israel Liberzon, K. Luan Phan, Clayton D. Scott
2012 J jnl
Robust kernel density estimation.
J. Mach. Learn. Res.
JooSeuk Kim, Clayton D. Scott
2012 — conf
Spatial Confidence Regions for Quantifying and Visualizing Registration Uncertainty.
WBIR
Takanori Watanabe, Clayton D. Scott
2011 J jnl
Asymptotic Source Detection Performance of Gamma-Ray Imaging Systems Under Model Mismatch.
IEEE Trans. Signal Process.
Daniel J. Lingenfelter, Jeffrey A. Fessler, Clayton D. Scott, Zhong He
2011 A* conf
On the Robustness of Kernel Density M-Estimators.
ICML
JooSeuk Kim, Clayton D. Scott
2011 J jnl
Robust Kernel Density Estimation
CoRR
JooSeuk Kim, Clayton D. Scott
2010 J jnl
Benefits of position-sensitive detectors for radioactive source detection.
IEEE Trans. Signal Process.
Daniel J. Lingenfelter, Jeffrey A. Fessler, Clayton D. Scott, Zhong He
2010 J jnl
L
IEEE Trans. Pattern Anal. Mach. Intell.
JooSeuk Kim, Clayton D. Scott
2010 J jnl
Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification.
IEEE Trans. Pattern Anal. Mach. Intell.
Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
2008 A* conf
Adaptive Hausdorff Estimation of Density Level Sets.
COLT
Aarti Singh, Robert D. Nowak, Clayton D. Scott
2008 A* conf
Distributed Spatial Anomaly Detection.
INFOCOM
Parminder Chhabra, Clayton D. Scott, Eric D. Kolaczyk, Mark Crovella
2008 Misc conf
Learning to satisfy.
ICASSP
Frederic Thouin, Mark Coates, Brian Eriksson, Robert D. Nowak, Clayton D. Scott
2008 — conf
Performance analysis for L_2 kernel classification.
NIPS
JooSeuk Kim, Clayton D. Scott
2008 Misc conf
Robust kernel density estimation.
ICASSP
JooSeuk Kim, Clayton D. Scott
2007 J jnl
Regression Level Set Estimation Via Cost-Sensitive Classification.
IEEE Trans. Signal Process.
Clayton D. Scott, Mark A. Davenport
2006 — conf
Controlling False Alarms With Support Vector Machines.
ICASSP (5)
Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
2006 J jnl
Learning Minimum Volume Sets.
J. Mach. Learn. Res.
Clayton D. Scott, Robert D. Nowak
2006 J jnl
Minimax-optimal classification with dyadic decision trees.
IEEE Trans. Inf. Theory
Clayton D. Scott, Robert D. Nowak
2006 J jnl
Robust Contour Matching Via the Order-Preserving Assignment Problem.
IEEE Trans. Image Process.
Clayton D. Scott, Robert D. Nowak
2005 J jnl
A Neyman-Pearson approach to statistical learning.
IEEE Trans. Inf. Theory
Clayton D. Scott, Robert D. Nowak
2005 — conf
Learning Minimum Volume Sets.
NIPS
Clayton D. Scott, Robert D. Nowak
2004 — conf
On the Adaptive Properties of Decision Trees.
NIPS
Clayton D. Scott, Robert D. Nowak
2004 J jnl
TEMPLAR: a wavelet-based framework for pattern learning and analysis.
IEEE Trans. Signal Process.
Clayton D. Scott, Robert D. Nowak
2003 — conf
CORT: classification or regression trees.
ICASSP (6)
Clayton D. Scott, Rebecca M. Willett, Robert D. Nowak
2003 — conf
Near-Minimax Optimal Classification with Dyadic Classification Trees.
NIPS
Clayton D. Scott, Robert D. Nowak
2002 — conf
Dyadic Classification Trees via Structural Risk Minimization.
NIPS
Clayton D. Scott, Robert D. Nowak
2000 — conf
A Novel Hierarchical Wavelet-Based Framework for Pattern Analysis and Synthesis.
SSIAI
Clayton D. Scott, Robert D. Nowak
2000 B conf
Pattern Extraction and Synthesis Using a Hierarchical Wavelet-Based Framework.
ICIP
Clayton D. Scott, Robert D. Nowak