Samory Kpotufe

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Sanjoy DasguptaProfessor of Computer Science, University of California, San DiegoVerified email at eng.ucsd.edu
Eric B. FlynnLos Alamos National LaboratoryVerified email at lanl.gov
Steve HannekePurdue UniversityVerified email at ttic.edu
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
Nakul VermaColumbia UniversityVerified email at cs.columbia.edu
Nick FeamsterNeubauer Professor of Computer Science, University of ChicagoVerified email at uchicago.edu
Kun YangPrinceton UniversityVerified email at princeton.edu
Guillaume G. MartinetPrinceton UniversityVerified email at princeton.edu
Heinrich JiangResearch Scientist, Google ResearchVerified email at google.com
Joe SukColumbia UniversityVerified email at columbia.edu
Andrea LocatelliOvGU MagdeburgVerified email at uni-potsdam.de
Kamalika ChaudhuriProfessor of Computer Science, UCSD. Research Scientist, Meta AIVerified email at ucsd.edu
Daniel HsuColumbia UniversityVerified email at cs.columbia.edu
Vikas GargMassachusetts Institute of Technology (MIT)Verified email at mit.edu
Dominik JanzingAmazon Development Center, TuebingenVerified email at amazon.com
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Abdeslam BoulariasRutgers UniversityVerified email at cs.rutgers.edu
Eloi FigueiredoFull Professor, Universidade Lusófona de Humanidades e TecnologiasVerified email at ulusofona.pt
Bharath SriperumbudurPennsylvania State UniversityVerified email at psu.edu
Shai Ben-DavidUniverity of Waterloo, CanadaVerified email at uwaterloo.ca

Samory Kpotufe

Columbia University

Verified email at columbia.edu - Homepage

Statistical Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Which spatial partition trees are adaptive to intrinsic dimension? N Verma, S Kpotufe, S Dasgupta arXiv preprint arXiv:1205.2609, 2012	95	2012
k-NN regression adapts to local intrinsic dimension S Kpotufe Advances in neural information processing systems 24, 2011	95	2011
Consistent procedures for cluster tree estimation and pruning K Chaudhuri, S Dasgupta, S Kpotufe, U Von Luxburg IEEE Transactions on Information Theory 60 (12), 7900-7912, 2014	78	2014
A different approach to sensor networking for SHM: Remote powering and interrogation with unmanned aerial vehicles M Todd, D Mascarenas, E Flynn, T Rosing, B Lee, D Musiani, S Dasgupta, ... 6th International Workshop on Structural Health Monitoring: Quantification …, 2007	72	2007
Pruning nearest neighbor cluster trees S Kpotufe, U Von Luxburg arXiv preprint arXiv:1105.0540, 2011	63	2011
Optimal rates for k-nn density and mode estimation S Dasgupta, S Kpotufe Advances in Neural Information Processing Systems 27, 2014	57	2014
On the value of target data in transfer learning S Hanneke, S Kpotufe Advances in Neural Information Processing Systems 32, 2019	52	2019
Adaptivity to local smoothness and dimension in kernel regression S Kpotufe, V Garg Advances in neural information processing systems 26, 2013	51	2013
A tree-based regressor that adapts to intrinsic dimension S Kpotufe, S Dasgupta Journal of Computer and System Sciences 78 (5), 1496-1515, 2012	51	2012
Consistency of causal inference under the additive noise model S Kpotufe, E Sgouritsa, D Janzing, B Schölkopf International Conference on Machine Learning, 478-486, 2014	49	2014
Marginal singularity, and the benefits of labels in covariate-shift S Kpotufe, G Martinet Conference On Learning Theory, 1882-1886, 2018	41	2018
A no-free-lunch theorem for multitask learning S Hanneke, S Kpotufe The Annals of Statistics 50 (6), 3119-3143, 2022	31	2022
Marginal singularity and the benefits of labels in covariate-shift S Kpotufe, G Martinet The Annals of Statistics 49 (6), 3299-3323, 2021	29	2021
Quickshift++: Provably good initializations for sample-based mean shift H Jiang, J Jang, S Kpotufe International Conference on Machine Learning, 2294-2303, 2018	29	2018
Adaptivity to noise parameters in nonparametric active learning A Locatelli, A Carpentier, S Kpotufe Proceedings of the 2017 Conference on Learning Theory, PMLR, 2017	29	2017
Modal-set estimation with an application to clustering H Jiang, S Kpotufe Artificial Intelligence and Statistics, 1197-1206, 2017	27	2017
An efficient one-class SVM for anomaly detection in the Internet of Things K Yang, S Kpotufe, N Feamster arXiv preprint arXiv:2104.11146, 2021	26	2021
Escaping the curse of dimensionality with a tree-based regressor S Kpotufe arXiv preprint arXiv:0902.3453, 2009	19	2009
Lipschitz density-ratios, structured data, and data-driven tuning S Kpotufe Artificial Intelligence and Statistics, 1320-1328, 2017	18	2017
Hierarchical label queries with data-dependent partitions S Kpotufe, R Urner, S Ben-David Conference on Learning Theory, 1176-1189, 2015	18	2015

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