Clustering-Based, Fully Automated Mixed-Bag Jigsaw Puzzle Solving. - Zayd Hammoudeh; Chris Pollett (CAIP (2), 2017)

Fast Sampling of Perfectly Uniform Satisfying Assignments. - Dimitris Achlioptas; Zayd S. Hammoudeh; Panos Theodoropoulos (SAT, 2018)

Fast and Flexible Probabilistic Model Counting. - Dimitris Achlioptas; Zayd Hammoudeh; Panos Theodoropoulos (SAT, 2018)

Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. - Zayd Hammoudeh; Daniel Lowd (NeurIPS, 2020)

On the Practicality of Learning Models for Network Telemetry. - Soheil Jamshidi; Zayd Hammoudeh; Ramakrishnan Durairajan; Daniel Lowd; Reza Rejaie; Walter Willinger (TMA, 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)

Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. - Zayd Hammoudeh; Daniel Lowd (CCS, 2022)

Reducing Certified Regression to Certified Classification. - Zayd Hammoudeh; Daniel Lowd (CoRR, 2022)

Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. - Wencong You; Zayd Hammoudeh; Daniel Lowd (EMNLP (Findings), 2023)

Reducing Certified Regression to Certified Classification for General Poisoning Attacks. - Zayd Hammoudeh; Daniel Lowd (SaTML, 2023)

Feature Partition Aggregation: A Fast Certified Defense Against a Union of Sparse Adversarial Attacks. - Zayd Hammoudeh; Daniel Lowd (CoRR, 2023)

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

Provable Robustness against a Union of L_0 Adversarial Attacks. - Zayd Hammoudeh; Daniel Lowd (AAAI, 2024)

Training data influence analysis and estimation: a survey. - Zayd Hammoudeh; Daniel Lowd (Mach. Learn., 2024)