Collective Classification of Social Network Spam. - Jonathan Brophy; Daniel Lowd (AAAI Workshops, 2017)

EGGS: A Flexible Approach to Relational Modeling of Social Network Spam. - Jonathan Brophy; Daniel Lowd (CoRR, 2020)

TREX: Tree-Ensemble Representer-Point Explanations. - Jonathan Brophy; Daniel Lowd (CoRR, 2020)

DART: Data Addition and Removal Trees. - Jonathan Brophy; Daniel Lowd (CoRR, 2020)

What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations. - Zhouhang Xie; Jonathan Brophy; Adam Noack; Wencong You; Kalyani Asthana; Carter Perkins; Sabrina Reis; Zayd Hammoudeh; Daniel Lowd; Sameer Singh 001 (BlackboxNLP@EMNLP, 2021)

Machine Unlearning for Random Forests. - Jonathan Brophy; Daniel Lowd (ICML, 2021)

Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees. - Jonathan Brophy; Daniel Lowd (NeurIPS, 2022)

Identifying Adversarial Attacks on Text Classifiers. - Zhouhang Xie; Jonathan Brophy; Adam Noack; Wencong You; Kalyani Asthana; Carter Perkins; Sabrina Reis; Sameer Singh 001; Daniel Lowd (CoRR, 2022)

TCAB: A Large-Scale Text Classification Attack Benchmark. - Kalyani Asthana; Zhouhang Xie; Wencong You; Adam Noack; Jonathan Brophy; Sameer Singh 001; Daniel Lowd (CoRR, 2022)

Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. - Jonathan Brophy; Zayd Hammoudeh; Daniel Lowd (J. Mach. Learn. Res., 2023)