5 citations · 6 across the 10 of their papers we have counts for
12 papers
Transfer Learning in Nonparametric Regression with Deep ReLU Networks
Junpeng Ren, Carlos Misael Madrid Padilla, Yanzhen Chen +1
This paper develops a general transfer learning framework for nonparametric regression with data consisting of multiple groups. Under the assumption that groups share a common stru…
Online Change Point Detection for Multivariate Inhomogeneous Poisson Processes Time Series
Xiaokai Luo, Haotian Xu, Carlos Misael Madrid Padilla +1
We study online change point detection for multivariate inhomogeneous Poisson point process time series. This setting arises commonly in applications such as earthquake seismology,…
Optimal Bias-variance Tradeoff in Matrix and Tensor Estimation
Shivam Kumar, Xiaokai Luo, Haotian Xu +3
We study matrix and tensor denoising when the underlying signal is \textbf{not} necessarily low-rank. In the tensor setting, we observe \[ Y = X^\ast + Z \in \mathbb{R}^{p_1 \times…
Risk Bounds For Distributional Regression
Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla, Sabyasachi Chatterjee
This work examines risk bounds for nonparametric distributional regression estimators. For convex-constrained distributional regression, general upper bounds are established for th…
Robust and Scalable Variational Bayes
Carlos Misael Madrid Padilla, Shitao Fan, Lizhen Lin
We propose a robust and scalable framework for variational Bayes (VB) that effectively handles outliers and contamination of arbitrary nature in large datasets. Our approach divide…
Multivariate Poisson intensity estimation via low-rank tensor decomposition
Haotian Xu, Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla +1
In this work, we propose new matrix- and tensor-based methodologies for estimating multivariate intensity functions of inhomogeneous point processes. By viewing multivariate intens…