Scalable-effort classifiers for energy-efficient machine learning

Proceedings - Design Automation Conference

Volumn 2015-June, Issue , 2015, Pages

  Venkataramani, Swagath ^a   Raghunathan, Anand ^a   Liu, Jie ^b   Shoaib, Mohammed ^b  

^a PURDUE UNIVERSITY   (United States)

^b MICROSOFT   (United States)

Author keywords

approximate computing; energy efficiency; input adaptive systems; machine learning classifiers

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CHAINS; COMPUTER AIDED DESIGN; ENERGY EFFICIENCY; LEARNING ALGORITHMS; LEARNING SYSTEMS; SUPERVISED LEARNING;

APPROXIMATE COMPUTING; CLASSIFICATION ALGORITHM; COMPUTATIONAL CAPABILITY; COMPUTATIONAL EFFORT; ENERGY-EFFICIENT MACHINE; HARDWARE AND SOFTWARE IMPLEMENTATIONS; REAL-WORLD DATASETS; SUPERVISED MACHINE LEARNING;

CLASSIFICATION (OF INFORMATION);

EID: 84951863284     PISSN: 0738100X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2744769.2744904     Document Type: Conference Paper

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