4 papers
Simulated Human Learning in a Dynamic, Partially-Observed, Time-Series Environment
Jeffrey Jiang, Kevin Hong, Emily Kuczynski +1
While intelligent tutoring systems (ITSs) can use information from past students to personalize instruction, each new student is unique. Moreover, the education problem is inherent…
PUREVQ-GAN: Defending Data Poisoning Attacks through Vector-Quantized Bottlenecks
Alexander Branch, Omead Pooladzandi, Radin Khosraviani +3
We introduce PureVQ-GAN, a defense against data poisoning that forces backdoor triggers through a discrete bottleneck using Vector-Quantized VAE with GAN discriminator. By quantizi…
PureEBM: Universal Poison Purification via Mid-Run Dynamics of Energy-Based Models
Omead Pooladzandi, Jeffrey Jiang, Sunay Bhat +1
Data poisoning attacks pose a significant threat to the integrity of machine learning models by leading to misclassification of target distribution data by injecting adversarial ex…
PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics
Sunay Bhat, Jeffrey Jiang, Omead Pooladzandi +2
Train-time data poisoning attacks threaten machine learning models by introducing adversarial examples during training, leading to misclassification. Current defense methods often…