Oscar Hernan Madrid Padilla

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Welcome!

I am a Tenure-track Assistant Professor in the Department of Statistics at University of California, Los Angeles. Previously, from July, 2017 to June, 2019, I was Neyman Visiting Assistant Professor in the Department of Statistics at University of California, Berkeley. Before that, I earned a Ph.D. in statistics at The University of Texas at Austin in May 2017 under the supervision of Prof. James Scott. My undergraudate degree was a B.S in Mathematics completed at CIMAT in April 2013, advised by Prof. Daniel Hernandez-Hernandez.

My research interests include:

A copy of my CV can be found here.

I was born and raised in Honduras.

Published/Accepted papers

O.H.M. Padilla, James Sharpnack, Yanzhen Chen, Daniela Witten. Adaptive Non-Parametric Regression With the K-NN Fused Lasso . To appear in Biometrika. arXiv.

O.H.M. Padilla, Alex Athey, Alex Reinhart, James G. Scott. Sequential nonparametric tests for a change in distribution: an application to detecting radiological anomalies. Journal of the American Statistical Association, Vol. 114, Issue 526, 514-528, 2019. Link.

O.H.M. Padilla, J. Sharpnack, J.G. Scott, and R.J Tibshirani. The DFS Fused Lasso: Linear-Time Denoising over General Graphs. Journal of Machine Learning Research, Vol. 18, No. 176, 1-36, 2018. Link.

O.H.M. Padilla, N.G. Polson and J.G. Scott. A deconvolution path to mixtures. Electronic Journal of Statistics Volume 12, Number 1 (2018), 1717-1751.

O.H.M. Padilla and J.G. Scott. Tensor decomposition with generalized lasso penalties. Journal of Computational and Graphical Statistics 2017, 26:3, 537-546. arXiv. Code.

D. Hernandez-Hernandez* and O.H.M. Padilla*. Worst portfolios for dynamic monetary utility processes. Stochastics, Vol. 90, Number 1 (2018), 78-101.

M. Zhou, O. H. M. Padilla, and J. G. Scott, “Priors for random count matrices derived from a family of negative binomial processes,” Journal of the American Statistical Association 2016, Vol. 111, No. 515, 1144-1156, Theory and Methods. PDF. Code.

W. Tansey, O.-H. Madrid-Padilla, A. Suggala, and P. Ravikumar. Vector-Space Markov Random Fields via Exponential Families.In International Conference on Machine Learning (ICML) 32, 2015. PDF. Code

Preprints

Alexandre Belloni* , Mingli Chen* , O. H. Madrid-Padilla* , Zixuan (Kevin) Wang* . High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing. Link

Marcos Matabuena , O. H. Madrid-Padilla . Energy distance and kernel mean embeddings for two-sample survival testing. Link

O.-H. Madrid-Padilla, Yi Yu, Carey E. Priebe. Change point localization in dependent dynamic nonparametric random dot product graphs. Link

O.-H. Madrid-Padilla, Yi Yu, Daren Wang, Alessandro Rinaldo. Optimal nonparametric multivariate change point detection and localization. Link

O.-H. Madrid-Padilla, Yi Yu, Daren Wang, Alessandro Rinaldo. Optimal nonparametric change point detection and localization. Link

Shitong Wei, O.-H. Madrid-Padilla, James Sharpnack. Distributed Cartesian Power Graph Segmentation for Graphon Estimation. Link.

O.-H. Madrid-Padilla. Graphon estimation via nearest neighbor algorithm and 2D fused lasso denoising. Link.

O.H.M. Padilla and J.G. Scott. Nonparametric density estimation by histogram trend filtering. Link.

*Alphabetical order.

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