A divide-and-conquer procedure for sparse inverse covariance estimation

Advances in Neural Information Processing Systems

Volumn 3, Issue , 2012, Pages 2330-2338

  Hsieh, Cho Jui ^a   Dhillon, Inderjit S ^a   Ravikumar, Pradeep ^a   Banerjee, Arindam ^b  

^a University of Texas at Austin   (United States)

^b University of Minnesota   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE SOLUTION; COMPUTATIONAL COSTS; COMPUTATIONAL PROCEDURES; GAUSSIAN MARKOV RANDOM FIELD; GAUSSIAN MAXIMUM LIKELIHOOD; OPTIMIZATION PROBLEMS; SPARSE INVERSE COVARIANCE MATRIXES; STATISTICAL GUARANTEE;

APPROXIMATION ALGORITHMS; CLUSTERING ALGORITHMS; COVARIANCE MATRIX; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION;

RANDOM VARIABLES;

EID: 84877783090     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

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