Seth Neel
13 papers · 2017–2026 · 7 venues · across top CS/AI venues
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Research topics
Machine Learning
(11)
Artificial Intelligence
(9)
Application Areas
(9)
Core AI
(9)
Optimization & Theory
(5)
Security & Privacy
(3)
Learning Types
(3)
Core Methods
(2)
Privacy
(2)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Applications
(1)
Differential Privacy
(1)
Learning Paradigms
(1)
Keywords
differential privacy
(4)
machine unlearning
(4)
large language model
(3)
privacy attack
(2)
empirical risk minimization
(2)
membership inference attack
(2)
data deletion
(2)
statistical indistinguishability
(2)
logistic regression
(1)
hypothesis testing
(1)
convex optimization
(1)
agnostic learning
(1)
linear regression
(1)
false positive rate
(1)
deep learning
(1)
data poisoning
(1)
zero-sum game
(1)
contextual bandit
(1)
bias mitigation
(1)
reservoir sampling
(1)
Papers
CheckMIABench: Firm Foundations For Membership Inference Attacks on Language Models
ACL 2026
Machine Unlearning Fails to Remove Data Poisoning Attacks
ICLR 2025
Machine Unlearning via Simulated Oracle Matching
ICLR 2025
Feature Importance Disparities for Data Bias Investigations
ICML 2024
In-Context Unlearning: Language Models as Few-Shot Unlearners
ICML 2024
MoPe: Model Perturbation based Privacy Attacks on Language Models
EMNLP 2023
On the Privacy Risks of Algorithmic Recourse
AISTATS 2023
Adaptive Machine Unlearning
NeurIPS 2021
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
ALT 2021
Oracle Efficient Private Non-Convex Optimization
ICML 2020
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
ICML 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
ICML 2018
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM
NeurIPS 2017