3 papers
cs.LG2026
MOONSHOT : A Framework for Multi-Objective Pruning of Vision and Large Language Models
Gabriel Afriat, Xiang Meng, Shibal Ibrahim +2
Weight pruning is a common technique for compressing large neural networks. We focus on the challenging post-training one-shot setting, where a pre-trained model is compressed with…
cs.LG2025
End-to-end Feature Selection Approach for Learning Skinny Trees
Shibal Ibrahim, Kayhan Behdin, Rahul Mazumder
We propose a new optimization-based approach for feature selection in tree ensembles, an important problem in statistics and machine learning. Popular tree ensemble toolkits e.g.,…
stat.ML2025
Predicting Census Survey Response Rates With Parsimonious Additive Models and Structured Interactions
Shibal Ibrahim, Peter Radchenko, Emanuel Ben-David +1
In this paper, we consider the problem of predicting survey response rates using a family of flexible and interpretable nonparametric models. The study is motivated by the US Censu…