activity
20192022
most citedPlug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations

3 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

A Deep Dive into Dataset Imbalance and Bias in Face Identification

Valeriia Cherepanova, Steven Reich, Samuel Dooley +3

As the deployment of automated face recognition (FR) systems proliferates, bias in these systems is not just an academic question, but a matter of public concern. Media portrayals…

cs.CV20223 cited

Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations

Amin Ghiasi, Hamid Kazemi, Steven Reich +3

Existing techniques for model inversion typically rely on hard-to-tune regularizers, such as total variation or feature regularization, which must be individually calibrated for ea…

cs.LG2020

Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast-Choose Three

Steven Reich, David Mueller, Nicholas Andrews

Modern neural networks do not always produce well-calibrated predictions, even when trained with a proper scoring function such as cross-entropy. In classification settings, simple…

cs.LG2020

Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks

Micah Goldblum, Steven Reich, Liam Fowl +3

Meta-learning algorithms produce feature extractors which achieve state-of-the-art performance on few-shot classification. While the literature is rich with meta-learning methods,…

cs.LG2019

WITCHcraft: Efficient PGD attacks with random step size

Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum +4

State-of-the-art adversarial attacks on neural networks use expensive iterative methods and numerous random restarts from different initial points. Iterative FGSM-based methods wit…