Algebraic Analysis for Nonidentifiable Learning Machines
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Publication:2731456
DOI10.1162/089976601300014402zbMath0985.68051OpenAlexW2120217353WikidataQ52066862 ScholiaQ52066862MaRDI QIDQ2731456
Publication date: 21 May 2002
Published in: Neural Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1162/089976601300014402
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Cites Work
- Stochastic complexity and modeling
- On zeta functions associated with prehomogeneous vector spaces
- B-functions and holonomic systems. Rationality of roots of B-functions
- Estimating the dimension of a model
- Algorithms for the \(b\)-function and \(D\)-modules associated with a polynomial
- Resolution of singularities of an algebraic variety over a field of characteristic zero. I
- On Hotelling's Approach to Testing for a Nonlinear Parameter in Regression
- An optimal selection of regression variables
- Testing in locally conic models, and application to mixture models
- A decision-theoretic extension of stochastic complexity and its applications to learning
- Resolution of Singularities and Division of Distributions
- A new look at the statistical model identification