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InfoGram and Admissible Machine Learning

InfoGram and Admissible Machine Learning

S. Mukhopadhyay
    FaML
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Papers citing "InfoGram and Admissible Machine Learning"

6 / 6 papers shown
Title
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence
Peter Stone
R. Brooks
Erik Brynjolfsson
Ryan Calo
Oren Etzioni
...
W. Press
A. Saxenian
J. Shah
Milind Tambe
Astro Teller
VLM
ELM
AI4TS
38
162
0
31 Oct 2022
How Costly is Noise? Data and Disparities in Consumer Credit
How Costly is Noise? Data and Disparities in Consumer Credit
Laura Blattner
Scott Nelson
38
43
0
17 May 2021
Ridge Regularizaton: an Essential Concept in Data Science
Ridge Regularizaton: an Essential Concept in Data Science
Trevor Hastie
20
82
0
30 May 2020
Breiman's "Two Cultures" Revisited and Reconciled
Breiman's "Two Cultures" Revisited and Reconciled
Subhadeep
S. Mukhopadhyay
Kaijun Wang
CML
VLM
34
4
0
27 May 2020
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations
Himabindu Lakkaraju
Osbert Bastani
56
254
0
15 Nov 2019
Confounding variables can degrade generalization performance of radiological deep learning models
Confounding variables can degrade generalization performance of radiological deep learning models
J. Zech
Marcus A. Badgeley
Manway Liu
A. Costa
J. Titano
Eric K. Oermann
OOD
80
1,173
0
02 Jul 2018