Padilla, Oscar Hernan Madrid

16 publications

TMLR 2025 Change Point Detection in Dynamic Graphs with Decoder-Only Latent Space Model Yik Lun Kei, Jialiang Li, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla

TMLR 2025 Change Point Detection on a Separable Model for Dynamic Networks Yik Lun Kei, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla

NeurIPS 2025 Network Two-Sample Test for Block Models Chung Kyong Nguen, Arash A. Amini, Oscar Hernan Madrid Padilla

AISTATS 2025 Quantile Additive Trend Filtering Zhi Zhang, Kyle Ritscher, Oscar Hernan Madrid Padilla

NeurIPS 2025 Risk Bounds for Distributional Regression Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla, Sabyasachi Chatterjee

AISTATS 2025 Statistical Guarantees for Lifelong Reinforcement Learning Using PAC-Bayes Theory Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla

JMLR 2024 Learning Gaussian DAGs from Network Data Hangjian Li, Oscar Hernan Madrid Padilla, Qing Zhou

JMLR 2024 Variance Estimation in Graphs with the Fused Lasso Oscar Hernan Madrid Padilla

NeurIPS 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

JMLR 2022 Change Point Localization in Dependent Dynamic Nonparametric Random Dot Product Graphs Oscar Hernan Madrid Padilla, Yi Yu, Carey E. Priebe

JMLR 2022 Extensions to the Proximal Distance Method of Constrained Optimization Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange

JMLR 2022 Quantile Regression with ReLU Networks: Estimators and Minimax Rates Oscar Hernan Madrid Padilla, Wesley Tansey, Yanzhen Chen

TMLR 2022 Sequentially Learning the Topological Ordering of Directed Acyclic Graphs with Likelihood Ratio Scores Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou

NeurIPS 2021 Lattice Partition Recovery with Dyadic CART Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo

JMLR 2021 Non-Parametric Quantile Regression via the K-NN Fused Lasso Steven Siwei Ye, Oscar Hernan Madrid Padilla

ICML 2015 Vector-Space Markov Random Fields via Exponential Families Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar