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09/14/2023
Flexible Functional Treatment Effect Estimation
We study treatment effect estimation with functional treatments where th...
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02/16/2023
Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior
Tensor regression methods have been widely used to predict a scalar resp...
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01/29/2023
Implicit Regularization for Group Sparsity
We study the implicit regularization of gradient descent towards structu...
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06/26/2022
Hierarchical nuclear norm penalization for multi-view data
The prevalence of data collected on the same set of samples from multipl...
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09/10/2021
Projected State-action Balancing Weights for Offline Reinforcement Learning
Offline policy evaluation (OPE) is considered a fundamental and challeng...
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08/12/2021
Implicit Sparse Regularization: The Impact of Depth and Early Stopping
In this paper, we study the implicit bias of gradient descent for sparse...
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06/09/2021
Matrix Completion with Model-free Weighting
In this paper, we propose a novel method for matrix completion under gen...
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03/05/2021
Estimation of Partially Conditional Average Treatment Effect by Hybrid Kernel-covariate Balancing
We study nonparametric estimation for the partially conditional average ...
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10/22/2020
CP Degeneracy in Tensor Regression
Tensor linear regression is an important and useful tool for analyzing t...
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09/24/2020
A Wavelet-Based Independence Test for Functional Data with an Application to MEG Functional Connectivity
Measuring and testing the dependency between multiple random functions i...
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08/29/2020
Broadcasted Nonparametric Tensor Regression
We propose a novel broadcasting idea to model the nonlinearity in tensor...
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08/29/2020
Low-Rank Covariance Function Estimation for Multidimensional Functional Data
Multidimensional function data arise from many fields nowadays. The cova...
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06/18/2020
Median Matrix Completion: from Embarrassment to Optimality
In this paper, we consider matrix completion with absolute deviation los...
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11/27/2019
Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis
A remarkable recent discovery in machine learning has been that deep neu...
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07/26/2019
Adjusting for Spatial Effects in Genomic Prediction
This paper investigates the problem of adjusting for spatial effects in ...
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12/19/2018
Matrix Completion under Low-Rank Missing Mechanism
This paper investigates the problem of matrix completion from corrupted ...
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09/03/2018
Network estimation via graphon with node features
Estimating the probabilities of linkages in a network has gained increas...
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06/02/2018
Autoencoders Learn Generative Linear Models
Recent progress in learning theory has led to the emergence of provable ...
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11/09/2017
Provably Accurate Double-Sparse Coding
Sparse coding is a crucial subroutine in algorithms for various signal p...
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03/01/2015
