The sparse regression cube: A reliable modeling technique for open cyber-physical systems

Proceedings - 2011 IEEE/ACM 2nd International Conference on Cyber-Physical Systems, ICCPS 2011

Volumn , Issue , 2011, Pages 87-96

  Ahmadi, Hossein ^a   Abdelzaher, Tarek ^a   Han, Jiawei ^a   Pham, Nam ^a   Ganti, Raghu K ^b  

^a University of Illinois at Urbana Champaign   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Cyber physical System; Data Cube; Linear Regression; Sparse Data

Indexed keywords

CARBON FOOTPRINT; COMPUTING TECHNOLOGY; CYBER-PHYSICAL SYSTEMS; DATA CUBE; EMPIRICAL REGRESSION MODEL; ESTIMATION THEORY; EVALUATION RESULTS; FIRST PRINCIPLE MODELS; HIERARCHICAL MODELING; HIGH EFFICIENCY; HIGH-DIMENSIONAL; LEVELS OF ABSTRACTION; LINEAR REGRESSION MODELS; MODELING ACCURACY; MODELING TECHNIQUE; PHYSICAL WORLD; PREDICTION ERRORS; RELIABLE MODELS; SPARSE DATA; SPARSE REGRESSION;

EMBEDDED SOFTWARE; EMBEDDED SYSTEMS; GEOMETRY; HIERARCHICAL SYSTEMS; LARGE SCALE SYSTEMS; MATHEMATICAL MODELS; REGRESSION ANALYSIS; UNCERTAINTY ANALYSIS;

MODELS;

EID: 79961146118     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCPS.2011.20     Document Type: Conference Paper

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