activity
20192026
most citedTE2Rules: Explaining Tree Ensembles using Rules

6 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Productionized Fairness Measurement Under Privacy Constraints

Osonde A. Osoba, Yuzi He, Saikrishna Badrinarayanan +3

Fairness measurements in the form of disaggregated evaluations often rely on demographic signals that are legally constrained or culturally sensitive. Race and ethnicity signals ar…

cs.LG2022★ 1 cited

NN2Rules: Extracting Rule List from Neural Networks

G Roshan Lal, Varun Mithal

We present an algorithm, NN2Rules, to convert a trained neural network into a rule list. Rule lists are more interpretable since they align better with the way humans make decision…

cs.LG2022★ 6 cited

TE2Rules: Explaining Tree Ensembles using Rules

G Roshan Lal, Xiaotong Chen, Varun Mithal

Tree Ensemble (TE) models, such as Gradient Boosted Trees, often achieve optimal performance on tabular datasets, yet their lack of transparency poses challenges for comprehending…

cs.LG2020

Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data

Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia +2

Many real-world phenomena are observed at multiple resolutions. Predictive models designed to predict these phenomena typically consider different resolutions separately. This appr…

cs.LG2019

An Attentive Survey of Attention Models

Sneha Chaudhari, Varun Mithal, Gungor Polatkan +1

Attention Model has now become an important concept in neural networks that has been researched within diverse application domains. This survey provides a structured and comprehens…