Themes: active learning, semi-supervised learning, transfer learning
Working papers:
Nicholas Galbraith, Samory Kpotufe. An Adaptive Classification Tree under Covariate-Shift.
Published papers:
Joe Suk, Samory Kpotufe. Tracking Most Severe Arm Changes in Bandits. COLT (to Appear) 2022.
[ arXiv ]
Samory Kpotufe, Gan Yuan, Yunfan Zhao. Nuances in Margin Conditions Determine Gains in Active Learning. AISTATS 2022.
[ arXiv ]
Steve Hanneke, Samory Kpotufe. A No-Free-Lunch Theorem For Multitask Learning. Annals of Statistics (to Appear) 2022. [ arXiv ]
Samory Kpotufe, Guillaume Martinet. Marginal Singularity, and the Benefits of Labels in Covariate-Shift. Annals of Statistics (to appear) 2021. [ arXiv ]
Joe Suk, Samory Kpotufe. Self-Tuning Bandits over Unknown Covariate-Shifts. Algorithmic Learning Theory (ALT) 2020.
[ arXiv ]
Steve Hanneke, Samory Kpotufe. On the Value of Target Data in Transfer Learning. Neural Information Processing Systems (NeurIPS) 2019.
[ pdf ]
Samory Kpotufe, Guillaume Martinet. Marginal Singularity, and the Benefits of Labels in Covariate-Shift. Accepted abstract at Conference on Learning Theory (COLT) 2018. [ arXiv ]
Andrea Locatelli, Alexandra, Carpentier, Samory Kpotufe. An Adaptive Strategy for Active Learning with Smooth Decision Boundary. Algorithmic Learning Theory (ALT) 2018.
[ arXiv ]
Andrea Locatelli, Alexandra, Carpentier, Samory Kpotufe. Adaptivity to Noise Parameters in Nonparametric Active Learning. Conference on Learning Theory (COLT) 2017.
[ pdf ]
Samory Kpotufe. Lipschitz Density-Ratios, Structured Data, and Data-driven Tuning. Artificial Intelligence and Statistics (AISTATS) 2017.
[ pdf ]
(Also listed under Unsupervised Learning)
Samory Kpotufe, Ruth Urner, Shai Ben-David. Hierarchical label queries with data-dependent partitions.
Conference on Learning Theory (COLT) 2015.
[ pdf ]