99 citations · 164 across the 5 of their papers we have counts for
6 papers
Learning Privately over Distributed Features: An ADMM Sharing Approach
Yaochen Hu, Peng Liu, Linglong Kong +1
Distributed machine learning has been widely studied in order to handle exploding amount of data. In this paper, we study an important yet less visited distributed learning problem…
Distributional Reinforcement Learning for Efficient Exploration
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao +3
In distributional reinforcement learning (RL), the estimated distribution of value function models both the parametric and intrinsic uncertainties. We propose a novel and efficient…
Sparse Wavelet Estimation in Quantile Regression with Multiple Functional Predictors
Dengdeng Yu, Li Zhang, Ivan Mizera +2
In this manuscript, we study quantile regression in partial functional linear model where response is scalar and predictors include both scalars and multiple functions. Wavelet bas…
Profile Estimation for Partial Functional Partially Linear Single-Index Model
Qingguo Tang, Linglong Kong, David Ruppert +1
This paper studies a \textit{partial functional partially linear single-index model} that consists of a functional linear component as well as a linear single-index component. This…
Local Region Sparse Learning for Image-on-Scalar Regression
Yao Chen, Xiao Wang, Linglong Kong +1
Identification of regions of interest (ROI) associated with certain disease has a great impact on public health. Imposing sparsity of pixel values and extracting active regions sim…
Multivariate varying coefficient model for functional responses
Hongtu Zhu, Runze Li, Linglong Kong
Motivated by recent work studying massive imaging data in the neuroimaging literature, we propose multivariate varying coefficient models (MVCM) for modeling the relation between m…