Clayton Scott

Affiliations:
  • University of Michigan, Ann Arbor, USA


According to our database1, Clayton Scott authored at least 88 papers between 2000 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Universal Feature Selection for Simultaneous Interpretability of Multitask Datasets.
CoRR, 2024

2023
Unified Binary and Multiclass Margin-Based Classification.
CoRR, 2023

Label Embedding by Johnson-Lindenstrauss Matrices.
CoRR, 2023

Mixture Proportion Estimation Beyond Irreducibility.
Proceedings of the International Conference on Machine Learning, 2023

On Classification-Calibration of Gamma-Phi Losses.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Learning from Label Proportions by Learning with Label Noise.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

VC dimension of partially quantized neural networks in the overparametrized regime.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Domain Generalization by Marginal Transfer Learning.
J. Mach. Learn. Res., 2021

An exact solver for the Weston-Watkins SVM subproblem.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Supervised PCA: A Multiobjective Approach.
CoRR, 2020

Weston-Watkins Hinge Loss and Ordered Partitions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning from Label Proportions: A Mutual Contamination Framework.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Calibrated Surrogate Losses for Adversarially Robust Classification.
Proceedings of the Conference on Learning Theory, 2020

2019
Decontamination of Mutual Contamination Models.
J. Mach. Learn. Res., 2019

Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions.
CoRR, 2019

PAC Reinforcement Learning without Real-World Feedback.
CoRR, 2019

A Generalization Error Bound for Multi-class Domain Generalization.
CoRR, 2019

Supervised Principal Component Analysis Via Manifold Optimization.
Proceedings of the IEEE Data Science Workshop, 2019

A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation.
Proceedings of the Algorithmic Learning Theory, 2019

Top Feasible Arm Identification.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Dictionary-Free MRI PERK: Parameter Estimation via Regression with Kernels.
IEEE Trans. Medical Imaging, 2018

Simple Regret Minimization for Contextual Bandits.
CoRR, 2018

Feasible Arm Identification.
Proceedings of the 35th International Conference on Machine Learning, 2018

Nonparametric Preference Completion.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Sparse Approximation of a Kernel Mean.
IEEE Trans. Signal Process., 2017

Adaptive Questionnaires for Direct Identification of Optimal Product Design.
CoRR, 2017

Consistent Kernel Density Estimation with Non-Vanishing Bandwidth.
CoRR, 2017

Multi-Task Learning for Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
On the consistency of inversion-free parameter estimation for Gaussian random fields.
J. Multivar. Anal., 2016

Mixture Proportion Estimation via Kernel Embedding of Distributions.
CoRR, 2016

Mixture Proportion Estimation via Kernel Embeddings of Distributions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
On The Identifiability of Mixture Models from Grouped Samples.
CoRR, 2015

Optimal change point detection in Gaussian processes.
CoRR, 2015

A Rate of Convergence for Mixture Proportion Estimation, with Application to Learning from Noisy Labels.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine.
NeuroImage, 2014

Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Scalable fused Lasso SVM for connectome-based disease prediction.
Proceedings of the IEEE International Conference on Acoustics, 2014

Scalable sparse approximation of a sample mean.
Proceedings of the IEEE International Conference on Acoustics, 2014

Class Proportion Estimation with Application to Multiclass Anomaly Rejection.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Decontamination of Mutually Contaminated Models.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
A Rank-Based Approach to Active Diagnosis.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Distributed effects of methylphenidate on the network structure of the resting brain: A connectomic pattern classification analysis.
NeuroImage, 2013

Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
CoRR, 2013

Semi-supervised Classification with Anomaly Rejection.
CoRR, 2013

Consistency of Robust Kernel Density Estimators.
Proceedings of the COLT 2013, 2013

Classification with Asymmetric Label Noise: Consistency and Maximal Denoising.
Proceedings of the COLT 2013, 2013

2012
Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations.
IEEE Trans. Inf. Theory, 2012

Transfer Learning for Auto-gating of Flow Cytometry Data.
Proceedings of the Unsupervised and Transfer Learning, 2012

Robust kernel density estimation.
J. Mach. Learn. Res., 2012

EM algorithms for multivariate Gaussian mixture models with truncated and censored data.
Comput. Stat. Data Anal., 2012

Spatial Confidence Regions for Quantifying and Visualizing Registration Uncertainty.
Proceedings of the Biomedical Image Registration - 5th International Workshop, 2012

2011
Asymptotic Source Detection Performance of Gamma-Ray Imaging Systems Under Model Mismatch.
IEEE Trans. Signal Process., 2011

Active Diagnosis under Persistent Noise with Unknown Noise Distribution: A Rank-Based Approach.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Statistical file matching of flow cytometry data.
J. Biomed. Informatics, 2011

Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks.
Proceedings of the UAI 2011, 2011

Generalizing from Several Related Classification Tasks to a New Unlabeled Sample.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Surrogate losses and regret bounds for cost-sensitive classification with example-dependent costs.
Proceedings of the 28th International Conference on Machine Learning, 2011

On the Robustness of Kernel Density M-Estimators.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Benefits of position-sensitive detectors for radioactive source detection.
IEEE Trans. Signal Process., 2010

Nested support vector machines.
IEEE Trans. Signal Process., 2010

L<sub>2</sub> Kernel Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

Semi-Supervised Novelty Detection.
J. Mach. Learn. Res., 2010

Query Learning with Exponential Query Costs
CoRR, 2010

Extensions of Generalized Binary Search to Group Identification and Exponential Costs.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Novelty detection: Unlabeled data definitely help.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Group-based Query Learning for rapid diagnosis in time-critical situations
CoRR, 2009

2008
Performance analysis for L_2 kernel classification.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Distributed Spatial Anomaly Detection.
Proceedings of the INFOCOM 2008. 27th IEEE International Conference on Computer Communications, 2008

Learning to satisfy.
Proceedings of the IEEE International Conference on Acoustics, 2008

Adaptive Hausdorff Estimation of Density Level Sets.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Regression Level Set Estimation Via Cost-Sensitive Classification.
IEEE Trans. Signal Process., 2007

Performance Measures for Neyman-Pearson Classification.
IEEE Trans. Inf. Theory, 2007

The One Class Support Vector Machine Solution Path.
Proceedings of the IEEE International Conference on Acoustics, 2007

2006
Minimax-optimal classification with dyadic decision trees.
IEEE Trans. Inf. Theory, 2006

Robust Contour Matching Via the Order-Preserving Assignment Problem.
IEEE Trans. Image Process., 2006

Learning Minimum Volume Sets.
J. Mach. Learn. Res., 2006

Controlling False Alarms With Support Vector Machines.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

2005
A Neyman-Pearson approach to statistical learning.
IEEE Trans. Inf. Theory, 2005

2004
TEMPLAR: a wavelet-based framework for pattern learning and analysis.
IEEE Trans. Signal Process., 2004

On the Adaptive Properties of Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Near-Minimax Optimal Classification with Dyadic Classification Trees.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

CORT: classification or regression trees.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

2002
Dyadic Classification Trees via Structural Risk Minimization.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2000
A Novel Hierarchical Wavelet-Based Framework for Pattern Analysis and Synthesis.
Proceedings of the 4th IEEE Southwest Symposium on Image Analysis and Interpretation, 2000

Pattern Extraction and Synthesis Using a Hierarchical Wavelet-Based Framework.
Proceedings of the 2000 International Conference on Image Processing, 2000


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