Wesley Tansey

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James G. ScottProfessor of Statistics and Data Science, University of Texas at AustinE-mail confirmado em mccombs.utexas.edu
David BleiProfessor of Statistics and Computer Science, Columbia UniversityE-mail confirmado em columbia.edu
Eli TilevichProfessor of Computer Science, Virginia TechE-mail confirmado em cs.vt.edu
Raul RabadanProfessor, Columbia UniversityE-mail confirmado em cumc.columbia.edu
Haoran ZhangThe University of Texas at AustinE-mail confirmado em cs.utexas.edu
Jesse ThomasonAssistant Professor, University of Southern CaliforniaE-mail confirmado em usc.edu
Eliana FeasleyKhan AcademyE-mail confirmado em khanacademy.org
Russ PoldrackProfessor of Psychology, Stanford UniversityE-mail confirmado em stanford.edu
Sanmi KoyejoAssistant Professor, University of Illinois at Urbana-ChampaignE-mail confirmado em illinois.edu
Victor VeitchUniversity of Chicago, GoogleE-mail confirmado em uchicago.edu
Risto MiikkulainenProfessor of Computer Science, the University of Texas at AustinE-mail confirmado em cs.utexas.edu
Karl PichottaMemorial Sloan Kettering Cancer CenterE-mail confirmado em mskcc.org
Yixin WangUniversity of California, BerkeleyE-mail confirmado em eecs.berkeley.edu
Alex ReinhartCarnegie Mellon UniversityE-mail confirmado em stat.cmu.edu
Alex AtheyUniversity of TexasE-mail confirmado em arlut.utexas.edu
Leif JohnsonWaymoE-mail confirmado em waymo.com
Igor V. KarpovGraduate Student, The University of Texas at AustinE-mail confirmado em cs.utexas.edu
Pradeep RavikumarAssociate Professor, School of Computer Science, Carnegie Mellon UniversityE-mail confirmado em cs.cmu.edu
Arun Sai SuggalaGoogle ResearchE-mail confirmado em google.com
Scott LindermanStanford UniversityE-mail confirmado em stanford.edu

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Wesley Tansey

Memorial Sloan Kettering Cancer Center

E-mail confirmado em mskcc.org - Página inicial

Machine Learning Bayesian Statistics Deep Learning Hypothesis Testing Computational Biology


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Annotation refactoring: inferring upgrade transformations for legacy applications W Tansey, E Tilevich Proceedings of the 23rd ACM SIGPLAN conference on Object-oriented …, 2008	59	2008
False Discovery Rate Smoothing W Tansey, O Koyejo, RA Poldrack, JG Scott Journal of the American Statistical Association 113 (523), 1156-1171, 2018	44*	2018
The Holdout Randomization Test for Feature Selection in Black Box Models W Tansey, V Veitch, H Zhang, R Rabadan, DM Blei Journal of Computational and Graphical Statistics, 2021	39*	2021
A fast and flexible algorithm for the graph-fused lasso W Tansey, JG Scott arXiv preprint arXiv:1505.06475, 2015	31	2015
Interpreting black box models via hypothesis testing C Burns, J Thomason, W Tansey Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference, 47-57, 2020	28*	2020
Multiscale spatial density smoothing: an application to large-scale radiological survey and anomaly detection W Tansey, A Athey, A Reinhart, JG Scott Journal of the American Statistical Association 112 (519), 1047-1063, 2017	25	2017
Efficient automated marshaling of C++ data structures for MPI applications W Tansey, E Tilevich 2008 IEEE International Symposium on Parallel and Distributed Processing, 1-12, 2008	25	2008
Vector-space Markov Random Fields via Exponential Families W Tansey, OHM Padilla, AS Suggala, P Ravikumar Proceedings of The 32nd International Conference on Machine Learning 37, 684-692, 2015	24	2015
Multiagent learning through neuroevolution R Miikkulainen, E Feasley, L Johnson, I Karpov, P Rajagopalan, A Rawal, ... IEEE World Congress on Computational Intelligence, 24-46, 2012	24	2012
Black Box FDR W Tansey, Y Wang, D Blei, R Rabadan International Conference on Machine Learning, 4867-4876, 2018	13	2018
Improved models for password guessing W Tansey University of Texas, Tech. Rep, 2011	9	2011
Leaf-smoothed hierarchical softmax for ordinal prediction W Tansey, K Pichotta, J Scott Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	8*	2018
Accelerating evolution via egalitarian social learning W Tansey, E Feasley, R Miikkulainen Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	8	2012
Dose–response modeling in high-throughput cancer drug screenings: an end-to-end approach W Tansey, K Li, H Zhang, SW Linderman, R Rabadan, DM Blei, ... Biostatistics 23 (2), 643-665, 2022	7*	2022
Quantile regression with deep ReLU Networks: Estimators and minimax rates OHM Padilla, W Tansey, Y Chen arXiv preprint arXiv:2010.08236, 2020	6	2020
Maximum-variance total variation denoising for interpretable spatial smoothing W Tansey, J Thomason, J Scott Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	6*	2018
Diet2Vec: Multi-scale analysis of massive dietary data W Tansey, EW Lowe Jr, JG Scott arXiv preprint arXiv:1612.00388, 2016	6	2016
DeXteR – An Extensible Framework for Declarative Parameter Passing in Distributed Object Systems S Gopal, W Tansey, GC Kannan, E Tilevich ACM/IFIP/USENIX International Conference on Distributed Systems Platforms …, 2008	5	2008
Deep direct likelihood knockoffs M Sudarshan, W Tansey, R Ranganath Advances in neural information processing systems 33, 5036-5046, 2020	4	2020
RankFromSets: Scalable set recommendation with optimal recall J Altosaar, R Ranganath, W Tansey Stat 10 (1), e363, 2021	3	2021

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