Zobrazeno 1 - 10
of 37
pro vyhledávání: '"McFowland III, Edward"'
Autor:
Akumu, Tanya, Cintas, Celia, Tadesse, Girmaw Abebe, Oshingbesan, Adebayo, Speakman, Skyler, McFowland III, Edward
The representations of the activation space of deep neural networks (DNNs) are widely utilized for tasks like natural language processing, anomaly detection and speech recognition. Due to the diverse nature of these tasks and the large size of DNNs,
Externí odkaz:
http://arxiv.org/abs/2312.08143
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To ad
Externí odkaz:
http://arxiv.org/abs/2306.13064
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterio
Externí odkaz:
http://arxiv.org/abs/2306.11181
Despite increasing popularity in empirical studies, the integration of machine learning generated variables into regression models for statistical inference suffers from the measurement error problem, which can bias estimation and threaten the validi
Externí odkaz:
http://arxiv.org/abs/2303.02820
With an increased focus on incorporating fairness in machine learning models, it becomes imperative not only to assess and mitigate bias at each stage of the machine learning pipeline but also to understand the downstream impacts of bias across stage
Externí odkaz:
http://arxiv.org/abs/2302.06752
Autor:
Cintas, Celia, Speakman, Skyler, Tadesse, Girmaw Abebe, Akinwande, Victor, McFowland III, Edward, Weldemariam, Komminist
Generative Adversarial Networks (GANs) have recently achieved unprecedented success in photo-realistic image synthesis from low-dimensional random noise. The ability to synthesize high-quality content at a large scale brings potential risks as the ge
Externí odkaz:
http://arxiv.org/abs/2105.12479
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to 'mine' variables of interest from availab
Externí odkaz:
http://arxiv.org/abs/2012.10790
Autor:
McFowland III, Edward1 emcfowland@hbs.edu, Gangarapu, Sandeep1 ganga020@umn.edu, Bapna, Ravi1 rbapna@umn.edu, Tianshu Sun2 tianshus@marshall.usc.edu
Publikováno v:
MIS Quarterly. Dec2021, Vol. 45 Issue 4, p1807-1832. 26p. 5 Diagrams, 8 Charts, 7 Graphs.
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detectio
Externí odkaz:
http://arxiv.org/abs/1804.01466
In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention's effects and which subpopulations to explicitly estimate. Moreover, the majority of the
Externí odkaz:
http://arxiv.org/abs/1803.09159