{"id":158178,"date":"2009-09-01T00:00:00","date_gmt":"2009-09-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/complexity-lower-bounds-using-linear-algebra\/"},"modified":"2018-10-16T20:42:28","modified_gmt":"2018-10-17T03:42:28","slug":"complexity-lower-bounds-using-linear-algebra","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/complexity-lower-bounds-using-linear-algebra\/","title":{"rendered":"Complexity Lower Bounds using Linear Algebra"},"content":{"rendered":"
Complexity Lower Bounds using Linear Algebra surveys several techniques for proving lower bounds in Boolean, algebraic, and communication complexity based on certain linear algebraic approaches. The common theme among these approaches is to study robustness measures of matrix rank that capture the complexity in a given model.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" Complexity Lower Bounds using Linear Algebra surveys several techniques for proving lower bounds in Boolean, algebraic, and communication complexity based on certain linear algebraic approaches. The common theme among these approaches is to study robustness measures of matrix rank that capture the complexity in a given 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