Neil G. Marchant

According to our database, Neil G. Marchant authored at least 10 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Adaptive Data Analysis for Growing Data.

Neil G. Marchant, Benjamin I. P. Rubinstein

CoRR, 2024

CERT-ED: Certifiably Robust Text Classification for Edit Distance.

Zhuoqun Huang, Neil G. Marchant, Olga Ohrimenko, Benjamin I. P. Rubinstein

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Certified Robustness of Learning-based Static Malware Detectors.

Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. P. Rubinstein

CoRR, 2023

Bayesian Graphical Entity Resolution Using Exchangeable Random Partition Priors.

Neil G. Marchant, Benjamin I. P. Rubinstein, Rebecca C. Steorts

CoRR, 2023

RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion.

Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. P. Rubinstein

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Hard to Forget: Poisoning Attacks on Certified Machine Unlearning.

Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

d-blink: Distributed End-to-End Bayesian Entity Resolution.

Neil G. Marchant, Andee Kaplan, Daniel N. Elazar, Benjamin I. P. Rubinstein, Rebecca C. Steorts

J. Comput. Graph. Stat., 2021

Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance.

Neil G. Marchant, Benjamin I. P. Rubinstein

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

A general framework for label-efficient online evaluation with asymptotic guarantees.

Neil G. Marchant, Benjamin I. P. Rubinstein

CoRR, 2020

2017

In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling.

Neil G. Marchant, Benjamin I. P. Rubinstein

Proc. VLDB Endow., 2017