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Neural Networks and Computational Learning Theory

 

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NeuroCOLT Technical Report NC-TR-96-052

Semi-Algebraic Complexity -- Additive Complexity of Diagonalization of QuadraticForms

Thomas Lickteig
Universit\"at Bonn
Germany

Klaus Meer
RWTH Aachen
Germany

Abstract (for references see full paper):
We study matrix calculation such as diagonalization of quadratic forms under the aspect of additive complexity and relate these complexities to the complexity of matrix multiplication. While in \cite{BKL} for multiplicative complexity the customary ``thick path existence'' argument was sufficient, here for additive complexity we need the more delicate finess of the real spectrum (cf. \cite{BCR}, \cite{Be}, \cite{KS}) to obtain a complexity relativization. After its outstanding success in semi-algebraic geometry the power of the real spectrum method in complexity theory becomes more and more apparent.   Our discussions substantiate once more the signification and future r\^ole of this concept in the mathematical evolution of the field of real algebraic algorithmic complexity.  A further technical tool concerning additive complexity is the structural transport metamorphosis from \cite{Li1} which constitutes another use of exponentiation and logarithm as it appears in the work on additive complexity by \cite{Gr} and \cite{Ri} through the use of \cite{Kh}.  We confine ourselves here to diagonalization of quadratic forms. In the forthcoming paper \cite{LM} further such relativizations of additive complexity will be given for a series of matrix computational tasks.

 

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