16 citations · 44 across the 13 of their papers we have counts for
6 papers · 1 filter
Sparsity-Constraint Optimization via Splicing Iteration
Jin Zhu, Junxian Zhu, Zezhi Wang +3
Sparsity-constrained optimization underlies many problems in signal processing, statistics, and machine learning. State-of-the-art hard-thresholding (HT) algorithms rely on an appr…
skscope: Fast Sparsity-Constrained Optimization in Python
Zezhi Wang, Jin Zhu, Peng Chen +5
Applying iterative solvers on sparsity-constrained optimization (SCO) requires tedious mathematical deduction and careful programming/debugging that hinders these solvers' broad im…
A Consistent and Scalable Algorithm for Best Subset Selection in Single Index Models
Borui Tang, Jin Zhu, Junxian Zhu +2
Analysis of high-dimensional data has led to increased interest in both single index models (SIMs) and the best-subset selection. SIMs provide an interpretable and flexible modelin…
Best-Subset Selection in Generalized Linear Models: A Fast and Consistent Algorithm via Splicing Technique
Junxian Zhu, Jin Zhu, Borui Tang +3
In high-dimensional generalized linear models, it is crucial to identify a sparse model that adequately accounts for response variation. Although the best subset section has been w…
abess: A Fast Best Subset Selection Library in Python and R
Jin Zhu, Xueqin Wang, Liyuan Hu +5
We introduce a new library named abess that implements a unified framework of best-subset selection for solving diverse machine learning problems, e.g., linear regression, classifi…
Computational analysis of pathological image enables interpretable prediction for microsatellite instability
Jin Zhu, Wangwei Wu, Yuting Zhang +4
Microsatellite instability (MSI) is associated with several tumor types and its status has become increasingly vital in guiding patient treatment decisions. However, in clinical pr…