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Papers
PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects
AAAI 2025
Strong Screening Rules for Group-based SLOPE Models
AISTATS 2025
A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
JMLR 2024
More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization
JMLR 2024
Sequential Gradient Descent and Quasi-Newton’s Method for Change-Point Analysis
AISTATS 2023
Generalized Sparse Additive Models
JMLR 2022
New Insights for the Multivariate Square-Root Lasso
JMLR 2022
Scalable Penalized Regression for Noise Detection in Learning With Noisy Labels
CVPR 2022
Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
NeurIPS 2021
A Regularization-Based Adaptive Test for High-Dimensional GLMs
JMLR 2020
Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices
COLT 2020
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
AISTATS 2020
High-Dimensional Interactions Detection with Sparse Principal Hessian Matrix
JMLR 2020
Variational Inference of Penalized Regression with Submodular Functions
UAI 2019
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
ICML 2018
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
ICML 2017
A New Algorithm and Theory for Penalized Regression-based Clustering
JMLR 2016
gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity
MLHC 2016
Structure-Leveraged Methods in Breast Cancer Risk Prediction
JMLR 2016
Trend Filtering on Graphs
JMLR 2016
Cluster Analysis: Unsupervised Learning via Supervised Learning with a Non-convex Penalty
JMLR 2013
Consistent Selection of Tuning Parameters via Variable Selection Stability
JMLR 2013
Reconciling "priors" & "priors" without prejudice?
NeurIPS 2013
Graphical Models via Generalized Linear Models
NeurIPS 2012