Wesley Tansey

2020

Deep Direct Likelihood Knockoffs

M. Sudarshan, W. Tansey, R. Ranganath

Preprint, August 2020.

[paper] [code]

Interpreting Black Box Models via Hypothesis Testing

C. Burns, J. Thomason, and W. Tansey

The 2020 ACM-IMS Foundations of Data Science Conference (FODS), October 2020.

[paper] [code]

RankFromSets: Scalable Set Recommendation with Optimal Recall

J. Altosaar, R. Ranganath, and W. Tansey

The 2020 ASA Symposium on Data Science and Statistics (SDSS), June 2020.

[paper coming soon] [code coming soon]

2019

Smoothed Nested Testing on Directed Acyclic Graphs

W. Tansey, J. H. Loper, L. Lei, and W. Fithian

Preprint, November 2019.

[paper] [code coming soon]

Relational Dose-Response Modeling for Cancer Drug Studies

W. Tansey, C. Tosh, and D. M. Blei

Preprint, November 2019.

[paper] [code]

2018

Dose-Response Modeling in High-Throughput Cancer Drug Screenings: An end-to-end approach

W. Tansey, K. Li, H. Zhang, S. W. Linderman, D. M. Blei, R. Rabadan, and C. H. Wiggins

Preprint, December 2018.

[paper] [code]

The Holdout Randomization Test: Principled and Easy Black Box Feature Selection

W. Tansey, V. Veitch, H. Zhang, R. Rabadan, and D. M. Blei

Preprint, November 2018.

[paper] [code]

Black Box FDR

W. Tansey, Y. Wang, D. M. Blei, and R. Rabadan

The 2018 International Conference on Machine Learning (ICML), July 2018.

[paper] [code]

Leaf-Smoothed Hierarchical Softmax for Ordinal Prediction

W. Tansey, K. Pichotta, and J. G. Scott

The 2018 AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.

[paper] [code]

Maximum-Variance Total Variation Denoising for Interpretable Spatial Smoothing

W. Tansey, J. Thomason, and J. G. Scott

The 2018 AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.

[paper] [code]

False Discovery Rate Smoothing.

W. Tansey, O. Koyejo, R. A. Poldrack, and J. G. Scott.

Journal of the American Statistical Association (JASA): Theory and Methods, 2018.

[paper] [code]

2017

Multiscale spatial density smoothing: an application to large-scale radiological survey and anomaly detection.

W. Tansey, A. Athey, A. Reinhart, and J. G. Scott

Journal of the American Statistical Association (JASA): Applications and Case Studies, 2017.

[paper] [code]

Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing

W. Tansey, J. Thomason, and J. G. Scott

The 2017 ICML Workshop on Human Interpretability in Machine Learning, August 2017.

Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning

W. Tansey, K. Pichotta, and J. G. Scott

Preprint, January 2017.

[paper] [code]

2016

Diet2Vec: Multi-scale analysis of massive dietary data

W. Tansey, E. W. Lowe, and J. G. Scott

The 2016 NIPS Workshop on Machine Learning for Health, December 2016.

[paper]

2015

A Fast and Flexible Algorithm for the Graph-Fused Lasso.

W. Tansey and J. G. Scott.

Preprint, May 2015.

[paper] [code]

Vector-Space Markov Random Fields via Exponential Families.

W. Tansey, O.-H. Madrid-Padilla, A. Suggala, and P. Ravikumar.

International Conference on Machine Learning (ICML) 32, 2015.

[paper] [code]

(-∞ - 2014]

Accelerating Evolution via Egalitarian Social Learning.

W. Tansey, E. Feasley, and R. Miikkulainen.

The 14th Annual Genetic and Evolutionary Computation Conference (GECCO'12), Philadelphia, Pennsylvania, USA, July 2012.

[paper] [code]

Multiagent learning through neuroevolution.

R. Miikkulainen, E. Feasley, L. Johnson, I. Karpov, P. Rajagopalan, A. Rawal, and W. Tansey.

Advances in Computational Intelligence, pages 24-46, 2012.

Trailblazer: A Tool for Automated Annotation Refactoring.

M. Song, E. Tilevich, and W. Tansey.

An OOPSLA 2009 Tool Demo., 2009.

DeXteR - An Extensible Framework for Declarative Parameter Passing in Distributed Object Systems.

S. Gopal, W. Tansey, G. C. Kannan, and E. Tilevich.

In Proceedings of ACM/IFIP/USENIX 9th International Middleware Conference (Middleware 2008), 2008.

[paper]

Annotation Refactoring: Inferring Upgrade Transformations for Legacy Applications.

W. Tansey and E. Tilevich.

In The 2008 ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA 2008), October 2008.

[paper]

Efficient Automated Marshaling of C++ Data Structures for MPI Applications.

W. Tansey and E. Tilevich.

In Proceedings of the 22nd Annual IEEE International Parallel and Distributed Processing Symposium (IPDPS 2008), April 2008.

[paper]