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Clayton Scott

29 papers · 2008–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (17) 🐝 Cross-Pollinator (13) πŸ† Keyword Champion πŸ”¬ Deep Specialist (13) πŸ“ˆ Trend Setter πŸ’Ž Century Club (29) πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (51)

Conferences

NIPS (9) AISTATS (6) ICML (5) JMLR (4) COLT (3) ALT (1) ICLR (1)

Top co-authors

Yutong Wang (6) Gilles Blanchard (6) Gyemin Lee (3) Aditya Gangrade (3) Julian Katz-Samuels (3) Venkatesh Saligrama (2) Suresh Bhavnani (2) Yilun Zhu (2) Robert A Vandermeulen (2) Gowtham Bellala (2)

Research topics

Statistics (1) Probability (1)

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