22 citations · 102 across the 31 of their papers we have counts for
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stat.ML2022
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari +1
Interpretable machine learning has demonstrated impressive performance while preserving explainability. In particular, neural additive models (NAM) offer the interpretability to th…
stat.ML2021★ 2 cited
Efficient Designs of SLOPE Penalty Sequences in Finite Dimension
Yiliang Zhang, Zhiqi Bu
In linear regression, SLOPE is a new convex analysis method that generalizes the Lasso via the sorted L1 penalty: larger fitted coefficients are penalized more heavily. This magnit…
stat.ML2019★ 6 cited
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
Zhiqi Bu, Jason Klusowski, Cynthia Rush +1
SLOPE is a relatively new convex optimization procedure for high-dimensional linear regression via the sorted l1 penalty: the larger the rank of the fitted coefficient, the larger…