10 citations · 29 across the 7 of their papers we have counts for
7 papers
TCAB: A Large-Scale Text Classification Attack Benchmark
Kalyani Asthana, Zhouhang Xie, Wencong You +4
We introduce the Text Classification Attack Benchmark (TCAB), a dataset for analyzing, understanding, detecting, and labeling adversarial attacks against text classifiers. TCAB inc…
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees
Jonathan Brophy, Daniel Lowd
Gradient-boosted regression trees (GBRTs) are hugely popular for solving tabular regression problems, but provide no estimate of uncertainty. We propose Instance-Based Uncertainty…
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees
Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
Influence estimation analyzes how changes to the training data can lead to different model predictions; this analysis can help us better understand these predictions, the models ma…
Identifying Adversarial Attacks on Text Classifiers
Zhouhang Xie, Jonathan Brophy, Adam Noack +6
The landscape of adversarial attacks against text classifiers continues to grow, with new attacks developed every year and many of them available in standard toolkits, such as Text…
Machine Unlearning for Random Forests
Jonathan Brophy, Daniel Lowd
Responding to user data deletion requests, removing noisy examples, or deleting corrupted training data are just a few reasons for wanting to delete instances from a machine learni…
TREX: Tree-Ensemble Representer-Point Explanations
Jonathan Brophy, Daniel Lowd
How can we identify the training examples that contribute most to the prediction of a tree ensemble? In this paper, we introduce TREX, an explanation system that provides instance-…
EGGS: A Flexible Approach to Relational Modeling of Social Network Spam
Jonathan Brophy, Daniel Lowd
Social networking websites face a constant barrage of spam, unwanted messages that distract, annoy, and even defraud honest users. These messages tend to be very short, making them…