
Fast Join Project Query Evaluation using Matrix Multiplication
In the last few years, much effort has been devoted to developing join a...
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Solving Linear Programs in the Current Matrix Multiplication Time
This paper shows how to solve linear programs of the form _Ax=b,x≥0 c^ x...
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Ranked Enumeration of Conjunctive Query Results
We investigate the enumeration of topk answers for conjunctive queries ...
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Parsing Linear ContextFree Rewriting Systems with Fast Matrix Multiplication
We describe a matrix multiplication recognition algorithm for a subset o...
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SpaceTime Tradeoffs for Answering Boolean Conjunctive Queries
In this paper, we investigate spacetime tradeoffs for answering boolean...
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Even Faster ElasticDegenerate String Matching via Fast Matrix Multiplication
An elasticdegenerate (ED) string is a sequence of n sets of strings of ...
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Asymmetric Random Projections
Random projections (RP) are a popular tool for reducing dimensionality w...
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Enumeration Algorithms for Conjunctive Queries with Projection
We investigate the enumeration of query results for an important subset of CQs with projections, namely star and path queries. The task is to design data structures and algorithms that allow for efficient enumeration with delay guarantees after a preprocessing phase. Our main contribution is a series of results based on the idea of interleaving precomputed output with further join processing to maintain delay guarantees, which maybe of independent interest. In particular, for star queries, we design combinatorial algorithms that provide instancespecific delay guarantees in linear preprocessing time. These algorithms improve upon the currently best known results. Further, we show how existing results can be improved upon by using fast matrix multiplication. We also present new results involving tradeoff between preprocessing time and delay guarantees for enumeration of path queries that contain projections. CQs with projection where the join attribute is projected away is equivalent to boolean matrix multiplication. Our results can therefore also be interpreted as sparse, outputsensitive matrix multiplication with delay guarantees.
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