Fairness-aware learning through regularization approach

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2011, Pages 643-650

  Kamishima, Toshihiro ^a   Akaho, Shotaro ^a   Sakuma, Jun ^b,c  

^a NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

^b UNIVERSITY OF TSUKUBA   (Japan)

^c JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

Author keywords

Classification; Discrimination; Fairness; Information theory; Logistic regression; Privacy

Indexed keywords

ANALYSIS TECHNIQUES; CLASSIFICATION RESULTS; CREDIT DATA; CREDIT SCORING; DATA MINING TECHNOLOGY; DISCRIMINATION; DISCRIMINATIVE MODELS; FAIRNESS; LOGISTIC REGRESSION; LOGISTIC REGRESSIONS; PREDICTION ALGORITHMS; PRIVACY PRESERVING; REGULARIZATION APPROACH; SENSITIVE FEATURES; SENSITIVE INFORMATIONS; SOCIAL RESPONSIBILITIES; STATISTICAL PREDICTION;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA PRIVACY; INFORMATION THEORY; LOGISTICS; REGRESSION ANALYSIS;

DATA MINING;

EID: 84857172480     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2011.83     Document Type: Conference Paper

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