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2020 – today
- 2024
[j2]Zayd Hammoudeh
, Daniel Lowd:
Training data influence analysis and estimation: a survey. Mach. Learn. 113(5): 2351-2403 (2024)- [c10]Zayd Hammoudeh, Daniel Lowd:
Provable Robustness against a Union of L_0 Adversarial Attacks. AAAI 2024: 21134-21142 - 2023
- [j1]Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd:
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. J. Mach. Learn. Res. 24: 154:1-154:48 (2023) - [c9]Wencong You, Zayd Hammoudeh, Daniel Lowd:
Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. EMNLP (Findings) 2023: 12499-12527 - [c8]Zayd Hammoudeh, Daniel Lowd:
Reducing Certified Regression to Certified Classification for General Poisoning Attacks. SaTML 2023: 484-523 - [i7]Zayd Hammoudeh, Daniel Lowd:
Feature Partition Aggregation: A Fast Certified Defense Against a Union of Sparse Adversarial Attacks. CoRR abs/2302.11628 (2023) - [i6]Wencong You, Zayd Hammoudeh, Daniel Lowd:
Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. CoRR abs/2310.18603 (2023) - 2022
- [c7]Zayd Hammoudeh, Daniel Lowd:
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. CCS 2022: 1367-1381 - [i5]Zayd Hammoudeh, Daniel Lowd:
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. CoRR abs/2201.10055 (2022) - [i4]Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd:
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. CoRR abs/2205.00359 (2022) - [i3]Zayd Hammoudeh, Daniel Lowd:
Reducing Certified Regression to Certified Classification. CoRR abs/2208.13904 (2022) - [i2]Zayd Hammoudeh, Daniel Lowd:
Training Data Influence Analysis and Estimation: A Survey. CoRR abs/2212.04612 (2022) - 2021
- [c6]Zhouhang Xie, Jonathan Brophy, Adam Noack, Wencong You, Kalyani Asthana, Carter Perkins, Sabrina Reis, Zayd Hammoudeh, Daniel Lowd, Sameer Singh:
What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations. BlackboxNLP@EMNLP 2021: 69-78 - 2020
- [c5]Zayd Hammoudeh, Daniel Lowd:
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. NeurIPS 2020 - [c4]Soheil Jamshidi, Zayd Hammoudeh, Ramakrishnan Durairajan, Daniel Lowd, Reza Rejaie, Walter Willinger:
On the Practicality of Learning Models for Network Telemetry. TMA 2020 - [i1]Zayd Hammoudeh, Daniel Lowd:
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. CoRR abs/2002.10261 (2020)
2010 – 2019
- 2018
- [c3]Dimitris Achlioptas, Zayd S. Hammoudeh, Panos Theodoropoulos:
Fast Sampling of Perfectly Uniform Satisfying Assignments. SAT 2018: 135-147 - [c2]Dimitris Achlioptas, Zayd Hammoudeh, Panos Theodoropoulos:
Fast and Flexible Probabilistic Model Counting. SAT 2018: 148-164 - 2017
- [c1]Zayd Hammoudeh, Chris Pollett:
Clustering-Based, Fully Automated Mixed-Bag Jigsaw Puzzle Solving. CAIP (2) 2017: 205-217
Coauthor Index
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last updated on 2024-09-13 00:37 CEST by the dblp team
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