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ORCIDOscar Hernan Madrid Padilla
Person information
- affiliation: University of California at Los Angeles, Department of Statistics, CA, USA
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2020 – today
- 2024
[j11]Oscar Hernan Madrid Padilla:
Variance estimation in graphs with the fused lasso. J. Mach. Learn. Res. 25: 250:1-250:45 (2024)- [j10]Yi Yu, Oscar Hernan Madrid Padilla, Daren Wang, Alessandro Rinaldo:
Network Online Change Point Localization. SIAM J. Math. Data Sci. 6(1): 176-198 (2024) - [i9]Marcos Matabuena, Juan Carlos Vidal, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela:
kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection. CoRR abs/2402.01635 (2024) - [i8]Chung Kyong Nguen, Oscar Hernan Madrid Padilla, Arash A. Amini:
Network two-sample test for block models. CoRR abs/2406.06014 (2024) - [i7]Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla:
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory. CoRR abs/2411.00401 (2024) - 2023
- [j9]Yik Lun Kei
, Yanzhen Chen, Oscar Hernan Madrid Padilla:
A partially separable model for dynamic valued networks. Comput. Stat. Data Anal. 187: 107811 (2023) - [j8]Lorenzo Cappello, Oscar Hernan Madrid Padilla, Julia A. Palacios:
Bayesian Change Point Detection with Spike-and-Slab Priors. J. Comput. Graph. Stat. 32(4): 1488-1500 (2023) - [c5]Carlos Misael Madrid Padilla, Haotian Xu, Daren Wang, Oscar Hernan Madrid Padilla, Yi Yu:
Change point detection and inference in multivariate non-parametric models under mixing conditions. NeurIPS 2023 - 2022
- [j7]Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange:
Extensions to the Proximal Distance Method of Constrained Optimization. J. Mach. Learn. Res. 23: 182:1-182:45 (2022) - [j6]Oscar Hernan Madrid Padilla, Yi Yu, Carey E. Priebe:
Change point localization in dependent dynamic nonparametric random dot product graphs. J. Mach. Learn. Res. 23: 234:1-234:59 (2022) - [j5]Oscar Hernan Madrid Padilla, Wesley Tansey, Yanzhen Chen:
Quantile regression with ReLU Networks: Estimators and minimax rates. J. Mach. Learn. Res. 23: 247:1-247:42 (2022) - [j4]Oscar Hernan Madrid Padilla, Yi Yu, Daren Wang, Alessandro Rinaldo:
Optimal Nonparametric Multivariate Change Point Detection and Localization. IEEE Trans. Inf. Theory 68(3): 1922-1944 (2022) - [j3]Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou:
Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores. Trans. Mach. Learn. Res. 2022 (2022) - [c4]Fan Wang, Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo:
Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients. AISTATS 2022: 4309-4338 - [c3]Yi Yu, Oscar Hernan Madrid Padilla, Alessandro Rinaldo:
Optimal partition recovery in general graphs. AISTATS 2022: 4339-4358 - [i6]Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou:
Sequential Learning of the Topological Ordering for the Linear Non-Gaussian Acyclic Model with Parametric Noise. CoRR abs/2202.01748 (2022) - [i5]Oscar Hernan Madrid Padilla:
Variance estimation in graphs with the fused lasso. CoRR abs/2207.12638 (2022) - 2021
- [j2]Steven Siwei Ye, Oscar Hernan Madrid Padilla:
Non-parametric Quantile Regression via the K-NN Fused Lasso. J. Mach. Learn. Res. 22: 111:1-111:38 (2021) - [c2]Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo:
Lattice partition recovery with dyadic CART. NeurIPS 2021: 26143-26155 - [i4]Yi Yu, Oscar Hernan Madrid Padilla, Daren Wang, Alessandro Rinaldo:
Optimal network online change point localisation. CoRR abs/2101.05477 (2021) - [i3]Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo:
Lattice partition recovery with dyadic CART. CoRR abs/2105.13504 (2021) - 2020
- [i2]Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange:
Extensions to the Proximal Distance of Method of Constrained Optimization. CoRR abs/2009.00801 (2020)
2010 – 2019
- 2018
- [i1]Shitong Wei, Oscar Hernan Madrid Padilla, James Sharpnack:
Distributed Cartesian Power Graph Segmentation for Graphon Estimation. CoRR abs/1805.09978 (2018) - 2017
- [j1]Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott, Ryan J. Tibshirani:
The DFS Fused Lasso: Linear-Time Denoising over General Graphs. J. Mach. Learn. Res. 18: 176:1-176:36 (2017) - 2015
- [c1]Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar:
Vector-Space Markov Random Fields via Exponential Families. ICML 2015: 684-692
Coauthor Index
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