Clayton Scott

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 39

Top Topics

Transfer Learning

Gaussian Process

Kernel Density Estimation

Top Venues

Publications

Matt Raymond, Angela Violi, Clayton Scott
Joint Optimization of Piecewise Linear Ensembles. CoRR (2024)
Matt Raymond, Jacob Charles Saldinger, Paolo Elvati, Clayton Scott, Angela Violi
Universal Feature Selection for Simultaneous Interpretability of Multitask Datasets. CoRR (2024)
Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott
Testing the Feasibility of Linear Programs with Bandit Feedback. CoRR (2024)
Yutong Wang, Clayton Scott
Unified Binary and Multiclass Margin-Based Classification. CoRR (2023)
Jianxin Zhang, Clayton Scott
Label Embedding by Johnson-Lindenstrauss Matrices. CoRR (2023)
Yilun Zhu, Aaron Fjeldsted, Darren Holland, George Landon, Azaree Lintereur, Clayton Scott
Mixture Proportion Estimation Beyond Irreducibility. ICML (2023)
Yilun Zhu, Aaron Fjeldsted, Darren Holland, George Landon, Azaree Lintereur, Clayton Scott
Mixture Proportion Estimation Beyond Irreducibility. CoRR (2023)
Yutong Wang, Clayton Scott
On Classification-Calibration of Gamma-Phi Losses. COLT (2023)
Jianxin Zhang, Yutong Wang, Clayton Scott
Learning from Label Proportions by Learning with Label Noise. CoRR (2022)
Yutong Wang, Clayton Scott
Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel. NeurIPS (2022)
Yutong Wang, Clayton Scott
VC dimension of partially quantized neural networks in the overparametrized regime. ICLR (2022)
Jianxin Zhang, Yutong Wang, Clayton Scott
Learning from Label Proportions by Learning with Label Noise. NeurIPS (2022)
Gilles Blanchard, Aniket Anand Deshmukh, Ürün Dogan, Gyemin Lee, Clayton Scott
Domain Generalization by Marginal Transfer Learning. J. Mach. Learn. Res. 22 (2021)
Yutong Wang, Clayton Scott
An exact solver for the Weston-Watkins SVM subproblem. ICML (2021)
Han Bao, Clayton Scott, Masashi Sugiyama
Calibrated Surrogate Losses for Adversarially Robust Classification. CoRR (2020)
Clayton Scott, Jianxin Zhang
Learning from Label Proportions: A Mutual Contamination Framework. CoRR (2020)
Han Bao, Clayton Scott, Masashi Sugiyama
Calibrated Surrogate Losses for Adversarially Robust Classification. COLT (2020)
Clayton Scott, Jianxin Zhang
Learning from Label Proportions: A Mutual Contamination Framework. NeurIPS (2020)
Yutong Wang, Clayton Scott
Weston-Watkins Hinge Loss and Ordered Partitions. NeurIPS (2020)
Julian Katz-Samuels, Gilles Blanchard, Clayton Scott
Decontamination of Mutual Contamination Models. J. Mach. Learn. Res. 20 (2019)
Julian Katz-Samuels, Clayton Scott
Top Feasible Arm Identification. AISTATS (2019)
Clayton Scott, Jianxin Zhang
Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions. CoRR (2019)
Yuren Zhong, Aniket Anand Deshmukh, Clayton Scott
PAC Reinforcement Learning without Real-World Feedback. CoRR (2019)
Aniket Anand Deshmukh, Yunwen Lei, Srinagesh Sharma, Ürün Dogan, James W. Cutler, Clayton Scott
A Generalization Error Bound for Multi-class Domain Generalization. CoRR (2019)
Clayton Scott
A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation. ALT (2019)
Clayton Scott
A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation. CoRR (2018)
Aniket Anand Deshmukh, Srinagesh Sharma, James W. Cutler, Mark Moldwin, Clayton Scott
Simple Regret Minimization for Contextual Bandits. CoRR (2018)
Julian Katz-Samuels, Clayton Scott
Feasible Arm Identification. ICML (2018)
Julian Katz-Samuels, Clayton Scott
Nonparametric Preference Completion. AISTATS (2018)
Aniket Anand Deshmukh, Ürün Dogan, Clayton Scott
Multi-Task Learning for Contextual Bandits. CoRR (2017)
Julian Katz-Samuels, Clayton Scott
Nonparametric Preference Completion. CoRR (2017)
Max Yi Ren, Clayton Scott
Adaptive Questionnaires for Direct Identification of Optimal Product Design. CoRR (2017)
Efrén Cruz Cortés, Clayton Scott
Consistent Kernel Density Estimation with Non-Vanishing Bandwidth. CoRR (2017)
Aniket Anand Deshmukh, Ürün Dogan, Clayton Scott
Multi-Task Learning for Contextual Bandits. NIPS (2017)
Efren Cruz Cortes, Clayton Scott
Sparse Approximation of a Kernel Mean. IEEE Trans. Signal Process. 65 (5) (2017)
Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
On the consistency of inversion-free parameter estimation for Gaussian random fields. J. Multivar. Anal. 150 (2016)
Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
On the consistency of inversion-free parameter estimation for Gaussian random fields. CoRR (2016)
Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari
Mixture Proportion Estimation via Kernel Embeddings of Distributions. ICML (2016)
Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari
Mixture Proportion Estimation via Kernel Embedding of Distributions. CoRR (2016)
Efren Cruz Cortes, Clayton Scott
Sparse Approximation of a Kernel Mean. CoRR (2015)
Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
Optimal change point detection in Gaussian processes. CoRR (2015)
Clayton Scott
A Rate of Convergence for Mixture Proportion Estimation, with Application to Learning from Noisy Labels. AISTATS (2015)
Efren Cruz Cortes, Clayton Scott
Scalable sparse approximation of a sample mean. ICASSP (2014)
Gilles Blanchard, Clayton Scott
Decontamination of Mutually Contaminated Models. AISTATS (2014)
Tyler Sanderson, Clayton Scott
Class Proportion Estimation with Application to Multiclass Anomaly Rejection. AISTATS (2014)
Clayton Scott, Gilles Blanchard, Gregory Handy, Sara Pozzi, Marek Flaska
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising CoRR (2013)
Tyler Sanderson, Clayton Scott
Semi-supervised Classification with Anomaly Rejection. CoRR (2013)
Clayton Scott, Gilles Blanchard, Gregory Handy
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising. COLT (2013)
Gowtham Bellala, Jason Stanley, Suresh K. Bhavnani, Clayton Scott
A Rank-Based Approach to Active Diagnosis. IEEE Trans. Pattern Anal. Mach. Intell. 35 (9) (2013)
Gowtham Bellala, Jason Stanley, Clayton Scott, Suresh K. Bhavnani
Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks CoRR (2012)
Gowtham Bellala, Suresh K. Bhavnani, Clayton Scott
Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations. IEEE Trans. Inf. Theory 58 (1) (2012)
Gyemin Lee, Lloyd Stoolman, Clayton Scott
Transfer Learning for Auto-gating of Flow Cytometry Data. ICML Unsupervised and Transfer Learning (2012)
Gyemin Lee, Clayton Scott
EM algorithms for multivariate Gaussian mixture models with truncated and censored data. Comput. Stat. Data Anal. 56 (9) (2012)
Gyemin Lee, William Finn, Clayton Scott
Statistical file matching of flow cytometry data. J. Biomed. Informatics 44 (4) (2011)
Clayton Scott
Surrogate losses and regret bounds for cost-sensitive classification with example-dependent costs. ICML (2011)
Gowtham Bellala, Suresh K. Bhavnani, Clayton Scott
Active Diagnosis under Persistent Noise with Unknown Noise Distribution: A Rank-Based Approach. AISTATS (2011)
Gilles Blanchard, Gyemin Lee, Clayton Scott
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample. NIPS (2011)
Gowtham Bellala, Jason Stanley, Clayton Scott, Suresh K. Bhavnani
Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks. UAI (2011)
Gyemin Lee, Clayton Scott
Nested support vector machines. IEEE Trans. Signal Process. 58 (3) (2010)
Gilles Blanchard, Gyemin Lee, Clayton Scott
Semi-Supervised Novelty Detection. J. Mach. Learn. Res. 11 (2010)
Gowtham Bellala, Suresh K. Bhavnani, Clayton Scott
Query Learning with Exponential Query Costs CoRR (2010)
Gowtham Bellala, Suresh K. Bhavnani, Clayton Scott
Extensions of Generalized Binary Search to Group Identification and Exponential Costs. NIPS (2010)
Gowtham Bellala, Suresh K. Bhavnani, Clayton Scott
Group-based Query Learning for rapid diagnosis in time-critical situations CoRR (2009)
Clayton Scott, Gilles Blanchard
Novelty detection: Unlabeled data definitely help. AISTATS (2009)
Gyemin Lee, Clayton Scott
Nested support vector machines. ICASSP (2008)
Clayton Scott
Performance Measures for Neyman-Pearson Classification. IEEE Trans. Inf. Theory 53 (8) (2007)
Gyemin Lee, Clayton Scott
The One Class Support Vector Machine Solution Path. ICASSP (2) (2007)