Escaping the Curse of Dimensionality with a Tree-based Regressor. - Samory Kpotufe (COLT, 2009)

Fast, smooth and adaptive regression in metric spaces. - Samory Kpotufe (NIPS, 2009)

Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? - Nakul Verma; Samory Kpotufe; Sanjoy Dasgupta (UAI, 2009)

The curse of dimension in nonparametric regression. - Samory Kpotufe (2010)

Pruning nearest neighbor cluster trees. - Samory Kpotufe; Ulrike von Luxburg (ICML, 2011)

k-NN Regression Adapts to Local Intrinsic Dimension. - Samory Kpotufe (NIPS, 2011)

Gradient Weights help Nonparametric Regressors. - Samory Kpotufe; Abdeslam Boularias (NIPS, 2012)

A tree-based regressor that adapts to intrinsic dimension. - Samory Kpotufe; Sanjoy Dasgupta (J. Comput. Syst. Sci., 2012)

Adaptivity to Local Smoothness and Dimension in Kernel Regression. - Samory Kpotufe; Vikas K. Garg 001 (NIPS, 2013)

Regression-tree Tuning in a Streaming Setting. - Samory Kpotufe; Francesco Orabona (NIPS, 2013)

Consistency of Causal Inference under the Additive Noise Model. - Samory Kpotufe; Eleni Sgouritsa; Dominik Janzing; Bernhard Schölkopf (ICML, 2014)

Optimal rates for k-NN density and mode estimation. - Sanjoy Dasgupta; Samory Kpotufe (NIPS, 2014)

A Consistent Estimator of the Expected Gradient Outerproduct. - Shubhendu Trivedi; Jialei Wang; Samory Kpotufe; Gregory Shakhnarovich (UAI, 2014)

Consistent Procedures for Cluster Tree Estimation and Pruning. - Kamalika Chaudhuri; Sanjoy Dasgupta; Samory Kpotufe; Ulrike von Luxburg (IEEE Trans. Inf. Theory, 2014)

Hierarchical Label Queries with Data-Dependent Partitions. - Samory Kpotufe; Ruth Urner; Shai Ben-David (COLT, 2015)

Gradients Weights improve Regression and Classification. - Samory Kpotufe; Abdeslam Boularias; Thomas Schultz 001; Kyoungok Kim (J. Mach. Learn. Res., 2016)

Modal-set estimation with an application to clustering. - Heinrich Jiang; Samory Kpotufe (AISTATS, 2017)

Lipschitz Density-Ratios, Structured Data, and Data-driven Tuning. - Samory Kpotufe (AISTATS, 2017)

Adaptivity to Noise Parameters in Nonparametric Active Learning. - Andrea Locatelli; Alexandra Carpentier; Samory Kpotufe (COLT, 2017)

Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality. - Samory Kpotufe; Nakul Verma (J. Mach. Learn. Res., 2017)

Achieving the time of 1-NN, but the accuracy of k-NN. - Lirong Xue; Samory Kpotufe (AISTATS, 2018)

An Adaptive Strategy for Active Learning with Smooth Decision Boundary. - Andrea Locatelli; Alexandra Carpentier; Samory Kpotufe (ALT, 2018)

Marginal Singularity, and the Benefits of Labels in Covariate-Shift. - Samory Kpotufe; Guillaume Martinet (COLT, 2018)

Quickshift++: Provably Good Initializations for Sample-Based Mean Shift. - Heinrich Jiang; Jennifer Jang; Samory Kpotufe (ICML, 2018)

PAC-Bayes Tree: weighted subtrees with guarantees. - Tin D. Nguyen; Samory Kpotufe (NeurIPS, 2018)

On the Value of Target Data in Transfer Learning. - Steve Hanneke; Samory Kpotufe (NeurIPS, 2019)

Kernel Sketching yields Kernel JL. - Samory Kpotufe; Bharath K. Sriperumbudur (CoRR, 2019)

Nearest Neighbor Classification and Search. - Sanjoy Dasgupta; Samory Kpotufe (Beyond the Worst-Case Analysis of Algorithms, 2020)

Gaussian Sketching yields a J-L Lemma in RKHS. - Samory Kpotufe; Bharath K. Sriperumbudur (AISTATS, 2020)

A No-Free-Lunch Theorem for MultiTask Learning. - Steve Hanneke; Samory Kpotufe (CoRR, 2020)

A Comparative Study of Network Traffic Representations for Novelty Detection. - Kun Yang; Samory Kpotufe; Nick Feamster (CoRR, 2020)

Self-Tuning Bandits over Unknown Covariate-Shifts. - Joseph Suk; Samory Kpotufe (ALT, 2021)

An Efficient One-Class SVM for Anomaly Detection in the Internet of Things. - Kun Yang; Samory Kpotufe; Nick Feamster (CoRR, 2021)

Tracking Most Severe Arm Changes in Bandits. - Joe Suk; Samory Kpotufe (CoRR, 2021)

Nuances in Margin Conditions Determine Gains in Active Learning. - Samory Kpotufe; Gan Yuan; Yunfan Zhao (AISTATS, 2022)

Tracking Most Significant Arm Switches in Bandits. - Joe Suk; Samory Kpotufe (COLT, 2022)

An Efficient One-Class SVM for Novelty Detection in IoT. - Kun Yang; Samory Kpotufe; Nick Feamster (Trans. Mach. Learn. Res., 2022)

Limits of Model Selection under Transfer Learning. - Steve Hanneke; Samory Kpotufe; Yasaman Mahdaviyeh (COLT, 2023)

Tracking Most Significant Shifts in Nonparametric Contextual Bandits. - Joe Suk; Samory Kpotufe (NeurIPS, 2023)

Nonlinear Meta-Learning Can Guarantee Faster Rates. - Dimitri Meunier; Zhu Li; Arthur Gretton; Samory Kpotufe (CoRR, 2023)

Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products. - Gan Yuan; Mingyue Xu; Samory Kpotufe; Daniel Hsu 001 (CoRR, 2023)

Tight Rates in Supervised Outlier Transfer Learning. - Mohammadreza M. Kalan; Samory Kpotufe (ICLR, 2024)

Distribution-Free Rates in Neyman-Pearson Classification. - Mohammadreza M. Kalan; Samory Kpotufe (CoRR, 2024)

A More Unified Theory of Transfer Learning. - Steve Hanneke; Samory Kpotufe (CoRR, 2024)

Regimes of No Gain in Multi-class Active Learning. - Gan Yuan; Yunfan Zhao; Samory Kpotufe (J. Mach. Learn. Res., 2024)

Classification Tree Pruning Under Covariate Shift. - Nicholas Galbraith; Samory Kpotufe (IEEE Trans. Inf. Theory, 2024)

Transfer Neyman-Pearson Algorithm for Outlier Detection. - Mohammadreza M. Kalan; Eitan J. Neugut; Samory Kpotufe (AISTATS, 2025)

Distributionally-Constrained Adversaries in Online Learning. - Moïse Blanchard; Samory Kpotufe (CoRR, 2025)

Mixed-Sample SGD: an End-to-end Analysis of Supervised Transfer Learning. - Yuyang Deng; Samory Kpotufe (CoRR, 2025)