Solving sparse linear equations over finite fields
IEEE Transactions on Information Theory
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SIAM Journal on Computing
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Acta Informatica
Solving homogeneous linear equations over GF(2) via block Wiedemann algorithm
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Efficient parallel solution of sparse systems of linear diophantine equations
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On Wiedemann's Method of Solving Sparse Linear Systems
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Black box linear algebra with the linbox library
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Proceedings of the 2006 international symposium on Symbolic and algebraic computation
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Proceedings of the 2007 international symposium on Symbolic and algebraic computation
Faster inversion and other black box matrix computations using efficient block projections
Proceedings of the 2007 international symposium on Symbolic and algebraic computation
Parallel computation of the rank of large sparse matrices from algebraic K-theory
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Solving structured linear systems with large displacement rank
Theoretical Computer Science
Fraction-free computation of simultaneous padé approximants
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Proceedings of the 2009 international symposium on Symbolic and algebraic computation
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Solving Very Sparse Rational Systems of Equations
ACM Transactions on Mathematical Software (TOMS)
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ACM Communications in Computer Algebra
Numeric-symbolic exact rational linear system solver
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Matrix sparsification and nested dissection over arbitrary fields
Journal of the ACM (JACM)
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We propose a new algorithm to find a rational solution to a sparse system of linear equations over the integers. This algorithm is based on a p-adic lifting technique combined with the use of block matrices with structured blocks. It achieves a sub-cubic complexity in terms of machine operations subject to a conjecture on the effectiveness of certain sparse projections. A LinBox-based implementation of this algorithm is demonstrated, and emphasizes the practical benefits of this new method over the previous state of the art.