Fairness in Learning: Classic and contextual bandits

Advances in Neural Information Processing Systems

Volumn , Issue , 2016, Pages 325-333

  Joseph, Matthew ^a   Kearns, Michael ^a   Morgenstern, Jamie ^a   Roth, Aaron ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUNCTIONS; PROBABILITY; STOCHASTIC SYSTEMS;

CONFIDENCE INTERVAL; CONTEXTUAL BANDITS; DIFFERENT CLASS; FAIR ALGORITHM; LEARNING MODELS; MULTI-ARMED BANDIT PROBLEM; NUMBER OF ARMS; STRONG SEPARATIONS;

LEARNING ALGORITHMS;

EID: 85018868407     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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