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Responses to Critiques on Machine Learning of Criminality Perceptions
  (Addendum of arXiv:1611.04135)

Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv:1611.04135)

13 November 2016
Xiaolin Wu
Xi Zhang
    CVBM
ArXivPDFHTML

Papers citing "Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv:1611.04135)"

8 / 8 papers shown
Title
Visual Privacy: Current and Emerging Regulations Around Unconsented
  Video Analytics in Retail
Visual Privacy: Current and Emerging Regulations Around Unconsented Video Analytics in Retail
S. Pletcher
11
4
0
24 Feb 2023
Goal Misgeneralization: Why Correct Specifications Aren't Enough For
  Correct Goals
Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals
Rohin Shah
Vikrant Varma
Ramana Kumar
Mary Phuong
Victoria Krakovna
J. Uesato
Zachary Kenton
40
68
0
04 Oct 2022
Accountability in an Algorithmic Society: Relationality, Responsibility,
  and Robustness in Machine Learning
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning
A. Feder Cooper
Emanuel Moss
Benjamin Laufer
Helen Nissenbaum
MLAU
32
85
0
10 Feb 2022
Pre-Trained Language Transformers are Universal Image Classifiers
Pre-Trained Language Transformers are Universal Image Classifiers
Rahul Goel
Modar Sulaiman
Kimia Noorbakhsh
Mahdieh Sharifi
Ragunath R. Sharma
Pooyan Jamshidi
Kallol Roy
ViT
30
2
0
25 Jan 2022
About Face: A Survey of Facial Recognition Evaluation
About Face: A Survey of Facial Recognition Evaluation
Inioluwa Deborah Raji
G. Fried
CVBM
30
54
0
01 Feb 2021
Pitfalls in Machine Learning Research: Reexamining the Development Cycle
Pitfalls in Machine Learning Research: Reexamining the Development Cycle
Stella Biderman
Walter J. Scheirer
24
26
0
04 Nov 2020
Theory In, Theory Out: The uses of social theory in machine learning for
  social science
Theory In, Theory Out: The uses of social theory in machine learning for social science
J. Radford
K. Joseph
8
44
0
09 Jan 2020
A Replication Study: Machine Learning Models Are Capable of Predicting
  Sexual Orientation From Facial Images
A Replication Study: Machine Learning Models Are Capable of Predicting Sexual Orientation From Facial Images
J. Leuner
CVBM
15
23
0
27 Feb 2019
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