Oscar Hernan Madrid Padilla

According to our database, Oscar Hernan Madrid Padilla authored at least 24 papers between 2015 and 2024.

Collaborative distances:

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

2024

Network Online Change Point Localization.

Yi Yu, Oscar Hernan Madrid Padilla, Daren Wang, Alessandro Rinaldo

SIAM J. Math. Data Sci., March, 2024

Variance estimation in graphs with the fused lasso.

Oscar Hernan Madrid Padilla

J. Mach. Learn. Res., 2024

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks.

Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla, Yik Lun Kei, Zhi Zhang, Yanzhen Chen

CoRR, 2024

Dense ReLU Neural Networks for Temporal-spatial Model.

Zhi Zhang, Carlos Misael Madrid Padilla, Xiaokai Luo, Oscar Hernan Madrid Padilla, Daren Wang

CoRR, 2024

Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory.

Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla

CoRR, 2024

Network two-sample test for block models.

Chung Kyong Nguen, Oscar Hernan Madrid Padilla, Arash A. Amini

CoRR, 2024

kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection.

Marcos Matabuena, Juan Carlos Vidal, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela

CoRR, 2024

2023

A partially separable model for dynamic valued networks.

Yik Lun Kei, Yanzhen Chen, Oscar Hernan Madrid Padilla

Comput. Stat. Data Anal., November, 2023

Bayesian Change Point Detection with Spike-and-Slab Priors.

Lorenzo Cappello, Oscar Hernan Madrid Padilla, Julia A. Palacios

J. Comput. Graph. Stat., 2023

Change point detection and inference in multivariate non-parametric models under mixing conditions.

Carlos Misael Madrid Padilla, Haotian Xu, Daren Wang, Oscar Hernan Madrid Padilla, Yi Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores.

Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou

Trans. Mach. Learn. Res., 2022

Optimal Nonparametric Multivariate Change Point Detection and Localization.

Oscar Hernan Madrid Padilla, Yi Yu, Daren Wang, Alessandro Rinaldo

IEEE Trans. Inf. Theory, 2022

Change point localization in dependent dynamic nonparametric random dot product graphs.

Oscar Hernan Madrid Padilla, Yi Yu, Carey E. Priebe

J. Mach. Learn. Res., 2022

Quantile regression with ReLU Networks: Estimators and minimax rates.

Oscar Hernan Madrid Padilla, Wesley Tansey, Yanzhen Chen

J. Mach. Learn. Res., 2022

Extensions to the Proximal Distance Method of Constrained Optimization.

Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange

J. Mach. Learn. Res., 2022

Sequential Learning of the Topological Ordering for the Linear Non-Gaussian Acyclic Model with Parametric Noise.

Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou

CoRR, 2022

Optimal partition recovery in general graphs.

Yi Yu, Oscar Hernan Madrid Padilla, Alessandro Rinaldo

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients.

Fan Wang, Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Non-parametric Quantile Regression via the K-NN Fused Lasso.

Steven Siwei Ye, Oscar Hernan Madrid Padilla

J. Mach. Learn. Res., 2021

Optimal network online change point localisation.

Yi Yu, Oscar Hernan Madrid Padilla, Daren Wang, Alessandro Rinaldo

CoRR, 2021

Lattice partition recovery with dyadic CART.

Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2018

Distributed Cartesian Power Graph Segmentation for Graphon Estimation.

Shitong Wei, Oscar Hernan Madrid Padilla, James Sharpnack

CoRR, 2018

2017

The DFS Fused Lasso: Linear-Time Denoising over General Graphs.

Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott, Ryan J. Tibshirani

J. Mach. Learn. Res., 2017

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