Search Results for: Planning machine tool
compressed linear algebra for large-scale machine learning compressed linear algebra for large-scale machine learning ahmed elgohary2*, matthias boehm1, peter j. haas1, frederick r. reiss1, berthold reinwald1 1 ibm research - almaden; san jose, ca, usa 2 university of maryland; college park, md, usa
abstract large-scale machine learning (ml) algorithms are often iterative, using repeated read-only data access and i/o- bound matrix-vector multiplications to converge to an opti- mal model. it is crucial for performance to fit the data into single-node or distributed main memory. general-purpose, heavy...
http://www.vldb.org/pvldb/vol9/p960-elgohary.pdf