Oscar Hernan Madrid Padilla

37 papers A* 3A 4Journal 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A causal fused lasso for interpretable heterogeneous treatment effects estimation. J. Mach. Learn. Res. Oscar Hernan Madrid Padilla, Yanzhen Chen, Carlos Misael Madrid Padilla, Gabriel Ruiz
2025	J	`jnl`	Bayesian Variance Change Point Detection With Credible Sets. IEEE Trans. Pattern Anal. Mach. Intell. Lorenzo Cappello, Oscar Hernan Madrid Padilla
2025	J	`jnl`	Bias-variance Tradeoff in Tensor Estimation. CoRR Shivam Kumar, Haotian Xu, Carlos Misael Madrid Padilla, Yuehaw Khoo, Oscar Hernan Madrid Padilla, Daren Wang
2025	J	`jnl`	Change Point Detection in Dynamic Graphs with Decoder-only Latent Space Model. Trans. Mach. Learn. Res. Yik Lun Kei, Jialiang Li, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla
2025	J	`jnl`	Change Point Detection on A Separable Model for Dynamic Networks. Trans. Mach. Learn. Res. Yik Lun Kei, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla
2025	J	`jnl`	Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces. CoRR Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela
2025	A	`conf`	Quantile Additive Trend Filtering. AISTATS Zhi Zhang, Kyle Ritscher, Oscar Hernan Madrid Padilla
2025	J	`jnl`	Risk Bounds For Distributional Regression. CoRR Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla, Sabyasachi Chatterjee
2025	A	`conf`	Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory. AISTATS Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla
2024	J	`jnl`	Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks. CoRR Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla, Yik Lun Kei, Zhi Zhang, Yanzhen Chen
2024	J	`jnl`	Dense ReLU Neural Networks for Temporal-spatial Model. CoRR Zhi Zhang, Carlos Misael Madrid Padilla, Xiaokai Luo, Oscar Hernan Madrid Padilla, Daren Wang
2024	J	`jnl`	Learning Gaussian DAGs from Network Data. J. Mach. Learn. Res. Hangjian Li, Oscar Hernan Madrid Padilla, Qing Zhou
2024	J	`jnl`	Network Online Change Point Localization. SIAM J. Math. Data Sci. Yi Yu, Oscar Hernan Madrid Padilla, Daren Wang, Alessandro Rinaldo
2024	J	`jnl`	Network two-sample test for block models. CoRR Chung Kyong Nguen, Oscar Hernan Madrid Padilla, Arash A. Amini
2024	J	`jnl`	Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory. CoRR Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla
2024	J	`jnl`	Variance estimation in graphs with the fused lasso. J. Mach. Learn. Res. Oscar Hernan Madrid Padilla
2024	J	`jnl`	kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection. CoRR Marcos Matabuena, Juan Carlos Vidal, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela
2023	J	`jnl`	A partially separable model for dynamic valued networks. Comput. Stat. Data Anal. Yik Lun Kei, Yanzhen Chen, Oscar Hernan Madrid Padilla
2023	J	`jnl`	Bayesian Change Point Detection with Spike-and-Slab Priors. J. Comput. Graph. Stat. Lorenzo Cappello, Oscar Hernan Madrid Padilla, Julia A. Palacios
2023	A*	`conf`	Change point detection and inference in multivariate non-parametric models under mixing conditions. NeurIPS Carlos Misael Madrid Padilla, Haotian Xu, Daren Wang, Oscar Hernan Madrid Padilla, Yi Yu
2022	J	`jnl`	Change point localization in dependent dynamic nonparametric random dot product graphs. J. Mach. Learn. Res. Oscar Hernan Madrid Padilla, Yi Yu, Carey E. Priebe
2022	A	`conf`	Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients. AISTATS Fan Wang, Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo
2022	J	`jnl`	Extensions to the Proximal Distance Method of Constrained Optimization. J. Mach. Learn. Res. Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange
2022	J	`jnl`	Optimal Nonparametric Multivariate Change Point Detection and Localization. IEEE Trans. Inf. Theory Oscar Hernan Madrid Padilla, Yi Yu, Daren Wang, Alessandro Rinaldo
2022	A	`conf`	Optimal partition recovery in general graphs. AISTATS Yi Yu, Oscar Hernan Madrid Padilla, Alessandro Rinaldo
2022	J	`jnl`	Quantile regression with ReLU Networks: Estimators and minimax rates. J. Mach. Learn. Res. Oscar Hernan Madrid Padilla, Wesley Tansey, Yanzhen Chen
2022	J	`jnl`	Sequential Learning of the Topological Ordering for the Linear Non-Gaussian Acyclic Model with Parametric Noise. CoRR Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou
2022	J	`jnl`	Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores. Trans. Mach. Learn. Res. Gabriel Ruiz, Oscar Hernan Madrid Padilla, Qing Zhou
2022	J	`jnl`	Variance estimation in graphs with the fused lasso. CoRR Oscar Hernan Madrid Padilla
2021	A*	`conf`	Lattice partition recovery with dyadic CART. NeurIPS Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo
2021	J	`jnl`	Lattice partition recovery with dyadic CART. CoRR Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo
2021	J	`jnl`	Non-parametric Quantile Regression via the K-NN Fused Lasso. J. Mach. Learn. Res. Steven Siwei Ye, Oscar Hernan Madrid Padilla
2021	J	`jnl`	Optimal network online change point localisation. CoRR Yi Yu, Oscar Hernan Madrid Padilla, Daren Wang, Alessandro Rinaldo
2020	J	`jnl`	Extensions to the Proximal Distance of Method of Constrained Optimization. CoRR Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange
2018	J	`jnl`	Distributed Cartesian Power Graph Segmentation for Graphon Estimation. CoRR Shitong Wei, Oscar Hernan Madrid Padilla, James Sharpnack
2017	J	`jnl`	The DFS Fused Lasso: Linear-Time Denoising over General Graphs. J. Mach. Learn. Res. Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott, Ryan J. Tibshirani
2015	A*	`conf`	Vector-Space Markov Random Fields via Exponential Families. ICML Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar