649 citations · 780 across the 20 of their papers we have counts for
7 papers · 1 filter
Privacy Blur: Quantifying Privacy and Utility for Image Data Release
Saeed Mahloujifar, Narine Kokhlikyan, Chuan Guo +1
Image data collected in the wild often contains private information such as faces and license plates, and responsible data release must ensure that this information stays hidden. A…
Z0-Inf: Zeroth Order Approximation for Data Influence
Narine Kokhlikyan, Kamalika Chaudhuri, Saeed Mahloujifar
A critical aspect of analyzing and improving modern machine learning systems lies in understanding how individual training examples influence a model's predictive behavior. Estimat…
Measuring Déjà vu Memorization Efficiently
Narine Kokhlikyan, Bargav Jayaraman, Florian Bordes +2
Recent research has shown that representation learning models may accidentally memorize their training data. For example, the déjà vu method shows that for certain representation l…
Error Discovery by Clustering Influence Embeddings
Fulton Wang, Julius Adebayo, Sarah Tan +2
We present a method for identifying groups of test examples -- slices -- on which a model under-performs, a task now known as slice discovery. We formalize coherence -- a requireme…
Bias Mitigation Framework for Intersectional Subgroups in Neural Networks
Narine Kokhlikyan, Bilal Alsallakh, Fulton Wang +3
We propose a fairness-aware learning framework that mitigates intersectional subgroup bias associated with protected attributes. Prior research has primarily focused on mitigating…
Investigating sanity checks for saliency maps with image and text classification
Narine Kokhlikyan, Vivek Miglani, Bilal Alsallakh +2
Saliency maps have shown to be both useful and misleading for explaining model predictions especially in the context of images. In this paper, we perform sanity checks for text mod…
Captum: A unified and generic model interpretability library for PyTorch
Narine Kokhlikyan, Vivek Miglani, Miguel Martin +8
In this paper we introduce a novel, unified, open-source model interpretability library for PyTorch [12]. The library contains generic implementations of a number of gradient and p…