no code implementations • 11 Apr 2024 • Brian Bell, Michael Geyer, David Glickenstein, Keaton Hamm, Carlos Scheidegger, Amanda Fernandez, Juston Moore
This article proposes a new framework for studying adversarial examples that does not depend directly on the distance to the decision boundary.
no code implementations • 2 Nov 2021 • Mateus Espadoto, Gabriel Appleby, Ashley Suh, Dylan Cashman, MingWei Li, Carlos Scheidegger, Erik W Anderson, Remco Chang, Alexandru C Telea
Projection techniques are often used to visualize high-dimensional data, allowing users to better understand the overall structure of multi-dimensional spaces on a 2D screen.
no code implementations • 18 Oct 2021 • MingWei Li, Carlos Scheidegger
Neural networks should be interpretable to humans.
no code implementations • 24 Nov 2020 • Thomas Matheson, Carl Stubens, Nicholas Wolf, Chien-Hsiu Lee, Gautham Narayan, Abhijit Saha, Adam Scott, Monika Soraisam, Adam S. Bolton, Benjamin Hauger, David R. Silva, John Kececioglu, Carlos Scheidegger, Richard Snodgrass, Patrick D. Aleo, Eric Evans-Jacquez, Navdeep Singh, Zhe Wang, Shuo Yang, Zhenge Zhao
We describe the Arizona-NOIRLab Temporal Analysis and Response to Events System (ANTARES), a software instrument designed to process large-scale streams of astronomical time-domain alerts.
Instrumentation and Methods for Astrophysics
no code implementations • ICML 2020 • I. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger, Sorelle Friedler
Game-theoretic formulations of feature importance have become popular as a way to "explain" machine learning models.
1 code implementation • NeurIPS 2019 • Charles T. Marx, Richard Lanas Phillips, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian
Specifically, we show that disentangled representations provide a mechanism to identify proxy features in the dataset, while allowing an explicit computation of feature influence on either individual outcomes or aggregate-level outcomes.
no code implementations • 9 Feb 2019 • Dylan Slack, Sorelle A. Friedler, Carlos Scheidegger, Chitradeep Dutta Roy
Through a user study with 1, 000 participants, we test whether humans perform well on tasks that mimic the definitions of simulatability and "what if" local explainability on models that are typically considered locally interpretable.
no code implementations • 28 Jan 2019 • Mohsen Abbasi, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian
While harms of allocation have been increasingly studied as part of the subfield of algorithmic fairness, harms of representation have received considerably less attention.
4 code implementations • 13 Feb 2018 • Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam Choudhary, Evan P. Hamilton, Derek Roth
Concretely, we present the results of an open benchmark we have developed that lets us compare a number of different algorithms under a variety of fairness measures, and a large number of existing datasets.
1 code implementation • 29 Jun 2017 • Danielle Ensign, Sorelle A. Friedler, Scott Neville, Carlos Scheidegger, Suresh Venkatasubramanian
Predictive policing systems are increasingly used to determine how to allocate police across a city in order to best prevent crime.
2 code implementations • 23 Sep 2016 • Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian
We show that in order to prove desirable properties of the entire decision-making process, different mechanisms for fairness require different assumptions about the nature of the mapping from construct space to decision space.
2 code implementations • 23 Feb 2016 • Philip Adler, Casey Falk, Sorelle A. Friedler, Gabriel Rybeck, Carlos Scheidegger, Brandon Smith, Suresh Venkatasubramanian
It is therefore hard to acquire a deeper understanding of model behavior, and in particular how different features influence the model prediction.
2 code implementations • 11 Dec 2014 • Michael Feldman, Sorelle Friedler, John Moeller, Carlos Scheidegger, Suresh Venkatasubramanian
It might not be possible to disclose the process.