Clayton Scott

1. Domain Generalization by Marginal Transfer Learning
   2017/11/21 by Gilles Blanchard, Blanchard, Gilles, Aniket Anand Deshmukh +7 · 11 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #Machine Learning and Data Classification
2. Classification with Asymmetric Label Noise: Consistency and Maximal\n Denoising
   2013/03/05 by Gilles Blanchard, Blanchard, Gilles, Marek Flaska +7 · 8 citations
   Computer Science · #Machine Learning and Data Classification #Machine Learning and Algorithms #Imbalanced Data Classification Techniques
3. Decontamination of Mutual Contamination Models
   2017/09/30 by Julian Katz-Samuels, Gilles Blanchard, Katz-Samuels, Julian +3 · 2 citations
   Computer Science · #Machine Learning and Data Classification #Machine Learning and Algorithms #Data Stream Mining Techniques
4. Label Noise: Ignorance Is Bliss
   2024/10/31 by Yilun Zhu, Jianxin Zhang, Zhu, Yilun +5 · 5 citations
   Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Music and Audio Processing
5. A Generalization Error Bound for Multi-class Domain Generalization
   2019/05/24 by Aniket Anand Deshmukh, Deshmukh, Aniket Anand, Yunwen Lei +9 · 3 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning and Algorithms #Machine Learning and ELM
6. On The Identifiability of Mixture Models from Grouped Samples
   2015/02/23 by Robert A. Vandermeulen, Vandermeulen, Robert A., Clayton Scott +1 · 1 citation
   Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Limits and Structures in Graph Theory #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Tensor decomposition and applications
7. Calibrated Surrogate Losses for Adversarially Robust Classification
   2020/05/28 by Han Bao, Bao, Han, Clayton Scott +3 · 1 citation
   Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Statistical Methods and Inference
8. Learning from Label Proportions by Learning with Label Noise
   2022/03/04 by Jianxin Zhang, Zhang, Jianxin, Yutong Wang +3 · 1 citation
   Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Human Pose and Action Recognition #Machine Learning (cs.LG) #Machine Learning and Data Classification
9. A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation
   2018/10/03 by Clayton Scott, Scott, Clayton · 2 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning and ELM