Quantile Regression with ReLU Networks: Estimators and minimax rates
Preprint, October 2020.
Quantile Regression with ReLU Networks: Estimators and minimax rates
Preprint, October 2020.
Smoothed Nested Testing on Directed Acyclic Graphs
Preprint, November 2019.
[paper] [code coming soon]
Relational Dose-Response Modeling for Cancer Drug Studies
Preprint, November 2019.
The Holdout Randomization Test: Principled and Easy Black Box Feature Selection
Preprint, November 2018.
Double Empirical Bayes Testing
International Statistical Review, 2020.
Dose-Response Modeling in High-Throughput Cancer Drug Screenings: An end-to-end approach
Biostatistics, 2020 (To Appear).
Deep Direct Likelihood Knockoffs
Neural Information Processing Systems (NeurIPS), 2020.
Interpreting Black Box Models via Hypothesis Testing
Foundations of Data Science (FODS), 2020.
RankFromSets: Scalable Set Recommendation with Optimal Recall
Stat, 2020 (To Appear).
[paper coming soon] [code]
Black Box FDR
International Conference on Machine Learning (ICML), 2018.
Leaf-Smoothed Hierarchical Softmax for Ordinal Prediction
AAAI Conference on Artificial Intelligence (AAAI), 2018.
Maximum-Variance Total Variation Denoising for Interpretable Spatial Smoothing
AAAI Conference on Artificial Intelligence (AAAI), 2018.
False Discovery Rate Smoothing.
Journal of the American Statistical Association (JASA): Theory and Methods, 2018.
Multiscale spatial density smoothing: an application to large-scale radiological survey and anomaly detection.
Journal of the American Statistical Association (JASA): Applications and Case Studies, 2017.
Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing
ICML Workshop on Human Interpretability in Machine Learning, 2017.
Diet2Vec: Multi-scale analysis of massive dietary data
NIPS Workshop on Machine Learning for Health, 2016.
[paper]
A Fast and Flexible Algorithm for the Graph-Fused Lasso.
Supplement to False Discovery Rate Smoothing, 2015.
Vector-Space Markov Random Fields via Exponential Families.
International Conference on Machine Learning (ICML), 2015.
Accelerating Evolution via Egalitarian Social Learning.
Genetic and Evolutionary Computation Conference (GECCO'12), 2012.
Multiagent learning through neuroevolution.
Advances in Computational Intelligence, pages 24-46, 2012.
Trailblazer: A Tool for Automated Annotation Refactoring.
An OOPSLA 2009 Tool Demo., 2009.
DeXteR - An Extensible Framework for Declarative Parameter Passing in Distributed Object Systems.
ACM/IFIP/USENIX International Middleware Conference (Middleware), 2008.
[paper]
Annotation Refactoring: Inferring Upgrade Transformations for Legacy Applications.
ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA), 2008.
[paper]
Efficient Automated Marshaling of C++ Data Structures for MPI Applications.
IEEE International Parallel and Distributed Processing Symposium (IPDPS 2008), 2008.
[paper]