scholarly journals Introductory Chapter: Machine Learning and Biometrics

Author(s):  
Jucheng Yang ◽  
Yarui Chen ◽  
Chuanlei Zhang ◽  
Dong Sun Park ◽  
Sook Yoon
Keyword(s):  

2021 ◽  
Author(s):  
Jaydip Sen ◽  
Rajdeep Sen ◽  
Abhishek Dutta





2020 ◽  
pp. 1-16
Author(s):  
Sarah Brayne

This introductory chapter provides a definition of big data as well as an overview of the use of big data in policing. Big data is a data environment made possible by the mass digitization of information and is associated with the use of advanced analytics, including network analysis and machine learning algorithms. Law enforcement’s adoption of big data is part of a broader shift toward the use of big data and machine-learned decisions throughout the criminal justice system. From surveillance to pretrial determinations and sentencing, big data saturates American criminal justice. It is also the subject of contentious debate in policy, media, legal, regulatory, advocacy, and academic circles. Focusing on the Los Angeles Police Department’s use of big data and associated surveillance technologies, this book studies how big data is actually used by police in practice—and to what consequence.



2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.



2020 ◽  
Author(s):  
Man-Wai Mak ◽  
Jen-Tzung Chien


2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  


2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
Keyword(s):  


Author(s):  
Lorenza Saitta ◽  
Attilio Giordana ◽  
Antoine Cornuejols


Author(s):  
Shai Shalev-Shwartz ◽  
Shai Ben-David
Keyword(s):  




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