Clayton D. Scott
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Clayton D. Scottcomputer-science Degrees
Computer Science
#6323
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Machine Learning
#2009
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#2035
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Artificial Intelligence
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#2299
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Database
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#3564
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Computer Science
Clayton D. Scott's Degrees
- PhD Computer Science Stanford University
- Masters Computer Science Stanford University
- Bachelors Computer Science Stanford University
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Why Is Clayton D. Scott Influential?
(Suggest an Edit or Addition)Clayton D. Scott's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- IEEE Transactions on Pattern Analysis and Machine Intelligence (2022) (1429)
- Robust kernel density estimation (2008) (305)
- Generalizing from Several Related Classification Tasks to a New Unlabeled Sample (2011) (300)
- Semi-Supervised Novelty Detection (2010) (245)
- Classification with Asymmetric Label Noise: Consistency and Maximal Denoising (2013) (210)
- A Neyman-Pearson approach to statistical learning (2005) (163)
- Learning Minimum Volume Sets (2005) (151)
- Mixture Proportion Estimation via Kernel Embeddings of Distributions (2016) (143)
- A Rate of Convergence for Mixture Proportion Estimation, with Application to Learning from Noisy Labels (2015) (131)
- Domain Generalization by Marginal Transfer Learning (2017) (127)
- EM algorithms for multivariate Gaussian mixture models with truncated and censored data (2012) (118)
- Minimax-optimal classification with dyadic decision trees (2006) (114)
- Robust contour matching via the order-preserving assignment problem (2006) (99)
- Adaptive Hausdorff Estimation of Density Level Sets (2009) (84)
- Calibrated asymmetric surrogate losses (2012) (82)
- The value of defibrillator electrograms for recognition of clinical ventricular tachycardias and for pace mapping of post-infarction ventricular tachycardia. (2010) (73)
- Multi-Task Learning for Contextual Bandits (2017) (73)
- Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification (2008) (72)
- Performance Measures for Neyman–Pearson Classification (2007) (72)
- Novelty detection: Unlabeled data definitely help (2009) (67)
- Distributed Spatial Anomaly Detection (2008) (66)
- Controlling False Alarms With Support Vector Machines (2006) (60)
- Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine (2013) (58)
- The One Class Support Vector Machine Solution Path (2007) (51)
- Automated analysis of the 12-lead electrocardiogram to identify the exit site of postinfarction ventricular tachycardia. (2012) (50)
- Class Proportion Estimation with Application to Multiclass Anomaly Rejection (2013) (49)
- Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations (2012) (40)
- Nested Support Vector Machines (2008) (37)
- Distributed effects of methylphenidate on the network structure of the resting brain: A connectomic pattern classification analysis (2013) (36)
- Regression Level Set Estimation Via Cost-Sensitive Classification (2007) (35)
- L₂ Kernel Classification (2010) (35)
- Machine learning for digital pulse shape discrimination (2012) (35)
- Dictionary-Free MRI PERK: Parameter Estimation via Regression with Kernels (2017) (32)
- Dyadic Classification Trees via Structural Risk Minimization (2002) (28)
- Optimal change point detection in Gaussian processes (2015) (28)
- Surrogate losses and regret bounds for cost-sensitive classification with example-dependent costs (2011) (28)
- A Generalization Error Bound for Multi-class Domain Generalization (2019) (26)
- Decontamination of Mutually Contaminated Models (2014) (24)
- Learning Minimum Volume Sets with Support Vector Machines (2006) (23)
- Decontamination of Mutual Contamination Models (2017) (22)
- Calibrated Surrogate Losses for Adversarially Robust Classification (2020) (22)
- A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation (2018) (21)
- Tree pruning with subadditive penalties (2005) (21)
- Statistical file matching of flow cytometry data (2010) (18)
- Sparse Approximation of a Kernel Mean (2015) (18)
- Near-Minimax Optimal Classification with Dyadic Classification Trees (2003) (17)
- Simple Regret Minimization for Contextual Bandits (2018) (17)
- Semi-Parametric Differential Expression Analysis via Partial Mixture Estimation (2008) (16)
- Consistency of Robust Kernel Density Estimators (2013) (16)
- Nonparametric Assessment of Contamination in Multivariate Data Using Generalized Quantile Sets and FDR (2010) (16)
- An operator theoretic approach to nonparametric mixture models (2016) (15)
- Hybrid Stem Cell States: Insights Into the Relationship Between Mammary Development and Breast Cancer Using Single-Cell Transcriptomics (2020) (15)
- TEMPLAR: a wavelet-based framework for pattern learning and analysis (2004) (14)
- Temporal Features and Kernel Methods for Predicting Sepsis in Postoperative Patients (2010) (14)
- Learning from Label Proportions: A Mutual Contamination Framework (2020) (13)
- Comparison and Design of Neyman-Pearson Classifiers (2005) (13)
- Extensions of Generalized Binary Search to Group Identification and Exponential Costs (2010) (13)
- Benefits of Position-Sensitive Detectors for Radioactive Source Detection (2010) (12)
- Transfer Learning for Auto-gating of Flow Cytometry Data (2011) (12)
- A Rank-Based Approach to Active Diagnosis (2013) (12)
- Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations (2020) (12)
- Nonparametric Preference Completion (2017) (11)
- Top Feasible Arm Identification (2019) (11)
- Feasible Arm Identification (2018) (11)
- The false discovery rate for statistical pattern recognition (2009) (10)
- On The Identifiability of Mixture Models from Grouped Samples (2015) (9)
- Nonparametric Assessment of Contamination in Multivariate Data Using Minimum Volume Sets and FDR (2007) (9)
- Spatial Confidence Regions for Quantifying and Visualizing Registration Uncertainty (2012) (9)
- Active Diagnosis under Persistent Noise with Unknown Noise Distribution: A Rank-Based Approach (2011) (9)
- CORT: classification or regression trees (2003) (8)
- On the Adaptive Properties of Decision Trees (2004) (8)
- Supervised Principal Component Analysis Via Manifold Optimization (2019) (8)
- Performance analysis for L_2 kernel classification (2008) (7)
- Asymptotic Source Detection Performance of Gamma-Ray Imaging Systems Under Model Mismatch (2011) (7)
- Scalable sparse approximation of a sample mean (2014) (7)
- Template Learning from Atomic Representations: A Wavelet-Based Approach to Pattern Analysis (2001) (7)
- Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space (2014) (6)
- Scalable fused Lasso SVM for connectome-based disease prediction (2014) (6)
- Transductive anomaly detection (2008) (6)
- On the Robustness of Kernel Density M-Estimators (2011) (6)
- Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks (2011) (6)
- Annotated Minimum Volume Sets for Nonparametric Anomaly Discovery (2007) (5)
- Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions (2019) (5)
- On the consistency of inversion-free parameter estimation for Gaussian random fields (2016) (5)
- Group-based Query Learning for rapid diagnosis in time-critical situations (2009) (5)
- Generalization Error Analysis for FDR Controlled Classification (2007) (4)
- Pattern extraction and synthesis using a hierarchical wavelet-based framework (2000) (4)
- Kernel Classification via Integrated Squared Error (2007) (4)
- Weston-Watkins Hinge Loss and Ordered Partitions (2020) (4)
- Minimax Support Vector Machines (2007) (4)
- A Mutual Contamination Analysis of Mixed Membership and Partial Label Models (2016) (4)
- Predicting ROC curves for source detection under model mismatch (2010) (3)
- Calibrated Surrogate Losses for Classification with Label-Dependent Costs (2010) (3)
- PAC Reinforcement Learning without Real-World Feedback (2019) (3)
- Learning from Label Proportions by Learning with Label Noise (2022) (3)
- Benefits of position-sensitive detectors for source detection with known background (2009) (2)
- Multisite Disease Classification with Functional Connectomes via Multitask Structured Sparse SVM (2014) (2)
- A novel hierarchical wavelet-based framework for pattern analysis and synthesis (2000) (2)
- Machine learning for flow cytometry data analysis (2011) (2)
- Source Detection Performance Prediction for a CdZnTe Array (2013) (2)
- Kernel methods for classification with irregularly sampled and contaminated data (2011) (2)
- A Scalable Preference Elicitation Algorithm Using Group Generalized Binary Search (2013) (2)
- Modified Group Generalized Binary Search with Near-Optimal Performance Guarantees (2010) (2)
- A gene filter for comparative analysis of single-cell RNA-sequencing trajectory datasets (2019) (2)
- VC dimension of partially quantized neural networks in the overparametrized regime (2021) (1)
- Adaptive Questionnaires for Direct Identification of Optimal Product Design (2017) (1)
- An exact solver for the Weston-Watkins SVM subproblem (2021) (1)
- Learning to satisfy (2008) (1)
- Supplemental Material for the AISTATS 2014 paper "Decontamination of Mutually Contaminated Models" (2014) (1)
- Classication with Asymmetric Label Noise: Consistency (2013) (1)
- Consistent Kernel Density Estimation with Non-Vanishing Bandwidth (2017) (1)
- Local inversion-free estimation of spatial Gaussian processes (2018) (1)
- Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel (2022) (1)
- Query Learning with Exponential Query Costs (2010) (1)
- Supplemental : Active Diagnosis via AUC Maximization (2011) (1)
- Semi-supervised Classification with Anomaly Rejection (2013) (0)
- Machine Learning Algorithms for Spacecraft Magnetic Field Interference Cancellation: Enabling Satellite Magnetometry without a Boom (2019) (0)
- Nonparametric Preference Completion : Supplementary Material (2018) (0)
- Surrogate losses for cost-sensitive classification with example-dependent costs (2011) (0)
- A pr 2 01 8 Nonparametric Preference Completion (0)
- Adaptive Minimax Classification with Dyadic Decision Trees (2004) (0)
- Supervised PCA: A Multiobjective Approach (2020) (0)
- Hierarchical wavelet-based image model for pattern analysis and synthesis (2000) (0)
- Tree pruning with sub-additive penalties (2004) (0)
- Detection performance prediction for CdZnTe array (2011) (0)
- Disease Prediction based on Functional Connectomes using a Spatially-Informed Fused Lasso Support Vector Classifier (2013) (0)
- Reproducing Kernel Hilbert Spaces (2014) (0)
- Submitted to the Annals of Statistics AN OPERATOR THEORETIC APPROACH TO NONPARAMETRIC MIXTURE MODELS By (2018) (0)
- Estimating Phase from Observed Trajectories Using the Temporal 1-Form (2022) (0)
- Reduced-complexity direction-of-arrival estimation for large-aperture antenna arrays employing spatial ambiguities (2016) (0)
- The Minimum Variance Unbiased Estimator Version 1 (2004) (0)
- Supplemental : A Rank-based Approach to Active Diagnosis (2012) (0)
- LEARNINGMINIMUM VOLUME SETSWITH SUPPORTVECTOR MACHINES (2011) (0)
- On Classification-Calibration of Gamma-Phi Losses (2023) (0)
- Sieve Estimators: Consistency and Rates of Convergence (2014) (0)
- Using wavelets to learn pattern templates (2002) (0)
- Feasible Arm Identification : Supplementary Material (2018) (0)
- On the consistency of inversion-free parameter estimation for Gaussian random fields (cid:73) (2016) (0)
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