1 citations · 1 across the 6 of their papers we have counts for
6 papers
Dynamic Incremental Optimization for Best Subset Selection
Shaogang Ren, Xiaoning Qian
Best subset selection is considered the `gold standard' for many sparse learning problems. A variety of optimization techniques have been proposed to attack this non-smooth non-con…
Causal Bayesian Optimization via Exogenous Distribution Learning
Shaogang Ren, Zihao Wang, Yuzhou Chen +1
Maximizing a target variable as an operational objective within a structural causal model is a fundamental problem. Causal Bayesian Optimization (CBO) approaches typically achieve…
Word Embedding with Neural Probabilistic Prior
Shaogang Ren, Dingcheng Li, Ping Li
To improve word representation learning, we propose a probabilistic prior which can be seamlessly integrated with word embedding models. Different from previous methods, word embed…
Variational Flow Graphical Model
Shaogang Ren, Belhal Karimi, Dingcheng Li +1
This paper introduces a novel approach to embed flow-based models with hierarchical structures. The proposed framework is named Variational Flow Graphical (VFG) Model. VFGs learn t…
Best Subset Selection with Efficient Primal-Dual Algorithm
Shaogang Ren, Guanhua Fang, Ping Li
Best subset selection is considered the `gold standard' for many sparse learning problems. A variety of optimization techniques have been proposed to attack this non-convex and NP-…
Safe Active Feature Selection for Sparse Learning
Shaogang Ren, Jianhua Z. Huang, Shuai Huang +1
We present safe active incremental feature selection~(SAIF) to scale up the computation of LASSO solutions. SAIF does not require a solution from a heavier penalty parameter as in…