Clayton Scott
29 papers · 2008–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (16) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (7)
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Academic Marathon
(17)
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Cross-Pollinator
(13)
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Keyword Champion
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Deep Specialist
(13)
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Trend Setter
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Century Club
(29)
π₯
Unstoppable
(8)
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Keyword Collector
(51)
Conferences
NIPS (9)
AISTATS (6)
ICML (5)
JMLR (4)
COLT (3)
ALT (1)
ICLR (1)
Top co-authors
Research topics
Keywords
label noise
(6)
multiclass classification
(5)
domain adaptation
(4)
support vector machine
(3)
binary classification
(3)
mixture model
(3)
reproducing kernel hilbert space
(3)
mixture proportion estimation
(3)
kernel density estimation
(3)
statistical learning
(3)
distribution estimation
(2)
active diagnosis
(2)
density estimation
(2)
kernel density estimator
(2)
novelty detection
(2)
semi-supervised learning
(2)
classification consistency
(2)
transfer learning
(2)
nonparametric estimation
(2)
robust estimation
(2)
Papers
Feasible Action Search for Bandit Linear Programs via Thompson Sampling
ICML 2025
Unified Binary and Multiclass Margin-Based Classification
JMLR 2024
The Implicit Bias of Gradient Descent on Separable Multiclass Data
NIPS 2024
Testing the Feasibility of Linear Programs with Bandit Feedback
ICML 2024
Label Noise: Ignorance Is Bliss
NIPS 2024
On Classification-Calibration of Gamma-Phi Losses
COLT 2023
Mixture Proportion Estimation Beyond Irreducibility
ICML 2023
VC dimension of partially quantized neural networks in the overparametrized regime
ICLR 2022
An exact solver for the Weston-Watkins SVM subproblem
ICML 2021
Domain Generalization by Marginal Transfer Learning
JMLR 2021
Learning from Label Proportions: A Mutual Contamination Framework
NIPS 2020
Weston-Watkins Hinge Loss and Ordered Partitions
NIPS 2020
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations
NIPS 2020
Top Feasible Arm Identification
AISTATS 2019
A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation
ALT 2019
Decontamination of Mutual Contamination Models
JMLR 2019
Nonparametric Preference Completion
AISTATS 2018
Mixture Proportion Estimation via Kernel Embeddings of Distributions
ICML 2016
A Rate of Convergence for Mixture Proportion Estimation, with Application to Learning from Noisy Labels
AISTATS 2015
Decontamination of Mutually Contaminated Models
AISTATS 2014
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space
NIPS 2014
Class Proportion Estimation with Application to Multiclass Anomaly Rejection
AISTATS 2014
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
COLT 2013
Consistency of Robust Kernel Density Estimators
COLT 2013
Active Diagnosis under Persistent Noise with Unknown Noise Distribution: A Rank-Based Approach
AISTATS 2011
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample
NIPS 2011
Semi-Supervised Novelty Detection
JMLR 2010
Extensions of Generalized Binary Search to Group Identification and Exponential Costs
NIPS 2010
Performance analysis for L\_2 kernel classification
NIPS 2008