Retail pricing for stochastic demand with unknown parameters: An online machine learning approach

2013 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013

Volumn , Issue , 2013, Pages 1353-1358

  Jia, Liyan ^a   Zhao, Qing ^a   Tong, Lang ^b  

^a Cornell University   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Demand response; electricity retail pricing; online learning; optimal stochastic thermal control; stochastic approximation

Indexed keywords

APPROXIMATION ALGORITHMS; APPROXIMATION THEORY; COMMERCE; COSTS; FUNCTIONS; LEARNING SYSTEMS; PIECEWISE LINEAR TECHNIQUES; SALES; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC SYSTEMS;

DEMAND RESPONSE; ONLINE LEARNING; RETAIL PRICING; STOCHASTIC APPROXIMATIONS; THERMAL CONTROL;

E-LEARNING;

EID: 84897687553     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/Allerton.2013.6736684     Document Type: Conference Paper

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