Wesley Tansey

According to our database, Wesley Tansey authored at least 20 papers between 2008 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

DIET: Conditional independence testing with marginal dependence measures of residual information.

Mukund Sudarshan, Aahlad Manas Puli, Wesley Tansey, Rajesh Ranganath

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Quantile regression with ReLU Networks: Estimators and minimax rates.

Oscar Hernan Madrid Padilla, Wesley Tansey, Yanzhen Chen

J. Mach. Learn. Res., 2022

The Holdout Randomization Test for Feature Selection in Black Box Models.

Wesley Tansey, Victor Veitch, Haoran Zhang, Raul Rabadan, David M. Blei

J. Comput. Graph. Stat., 2022

Targeted active learning for probabilistic models.

Christopher Tosh, Mauricio Tec, Wesley Tansey

CoRR, 2022

2020

Deep Direct Likelihood Knockoffs.

Mukund Sudarshan, Wesley Tansey, Rajesh Ranganath

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Interpreting Black Box Models via Hypothesis Testing.

Collin Burns, Jesse Thomason, Wesley Tansey

Proceedings of the FODS '20: ACM-IMS Foundations of Data Science Conference, 2020

2019

Selected Papers from the Workshop on Computational Biology: Joint with the International Joint Conference on Artificial Intelligence and the International Conference on Machine Learning, 2018.

Abdoulaye Baniré Diallo, Engelbert Mephu Nguifo, Wajdi Dhifli, Elham Azizi, Sandhya Prabhakaran, Wesley Tansey

J. Comput. Biol., 2019

Bayesian Tensor Filtering: Smooth, Locally-Adaptive Factorization of Functional Matrices.

Wesley Tansey, Christopher Tosh, David M. Blei

CoRR, 2019

Interpreting Black Box Models with Statistical Guarantees.

Collin Burns, Jesse Thomason, Wesley Tansey

CoRR, 2019

2018

Black Box FDR.

Wesley Tansey, Yixin Wang, David M. Blei, Raul Rabadan

Proceedings of the 35th International Conference on Machine Learning, 2018

Maximum-Variance Total Variation Denoising for Interpretable Spatial Smoothing.

Wesley Tansey, Jesse Thomason, James G. Scott

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Leaf-Smoothed Hierarchical Softmax for Ordinal Prediction.

Wesley Tansey, Karl Pichotta, James G. Scott

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016

Diet2Vec: Multi-scale analysis of massive dietary data.

Wesley Tansey, Edward W. Lowe Jr., James G. Scott

CoRR, 2016

2015

Vector-Space Markov Random Fields via Exponential Families.

Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar

Proceedings of the 32nd International Conference on Machine Learning, 2015

2012

Multiagent Learning through Neuroevolution.

Risto Miikkulainen, Eliana Feasley, Leif M. Johnson, Igor Karpov, Padmini Rajagopalan, Aditya Rawal, Wesley Tansey

Proceedings of the Advances in Computational Intelligence, 2012

Accelerating evolution via egalitarian social learning.

Wesley Tansey, Eliana Feasley, Risto Miikkulainen

Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2009

Trailblazer: a tool for automated annotation refactoring.

Myoungkyu Song, Eli Tilevich, Wesley Tansey

Proceedings of the Companion to the 24th Annual ACM SIGPLAN Conference on Object-Oriented Programming, 2009

2008

Annotation refactoring: inferring upgrade transformations for legacy applications.

Wesley Tansey, Eli Tilevich

Proceedings of the 23rd Annual ACM SIGPLAN Conference on Object-Oriented Programming, 2008

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

Sriram Gopal, Wesley Tansey, Gokulnath C. Kannan, Eli Tilevich

Proceedings of the Middleware 2008, 2008

Efficient automated marshaling of C++ data structures for MPI applications.

Wesley Tansey, Eli Tilevich

Proceedings of the 22nd IEEE International Symposium on Parallel and Distributed Processing, 2008