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Gaussian Certified Unlearning in High Dimensions: A Hypothesis Testing Approach
Aaradhya Pandey, Arnab Auddy, Haolin Zou +2
Machine unlearning seeks to efficiently remove the influence of selected data while preserving generalization. Significant progress has been made in low dimensions , but…
Newfluence: Boosting Model interpretability and Understanding in High Dimensions
Haolin Zou, Arnab Auddy, Yongchan Kwon +2
The increasing complexity of machine learning (ML) and artificial intelligence (AI) models has created a pressing need for tools that help scientists, engineers, and policymakers i…
Multilook Coherent Imaging: Theoretical Guarantees and Algorithms
Xi Chen, Soham Jana, Christopher A. Metzler +2
Multilook coherent imaging is a widely used technique in applications such as digital holography, ultrasound imaging, and synthetic aperture radar. A central challenge in these sys…
Certified Data Removal Under High-dimensional Settings
Haolin Zou, Arnab Auddy, Yongchan Kwon +2
Machine unlearning focuses on the computationally efficient removal of specific training data from trained models, ensuring that the influence of forgotten data is effectively elim…