Abstract:This paper contains a short and simplified proof of desingularization over fields of characteristic zero, together with various applications to other problems in algebraic geometry (among others, the study of the behavior of desingularization of families of embedded schemes, and a formulation of desingularization which is stronger than Hironaka's). Our proof avoids the use of the Hilbert-Samuel function and Hironaka's notion of normal flatness: First we define a procedure for principalization of ideals (i. e. … Show more
“…Thus, we can ignore the origin in computing the RLCT. All other points on the exceptional divisor of this blowup lie on some other chart of the blowup where the pullback pair is (s; s 6 ), so the RLCT is at least (7,1). In the chart where…”
Section: Appendicesmentioning
confidence: 99%
“…While general algorithms exist for monomializing any analytic function [7,4], applying them to nonpolynomial functions such as K(ω) can be computationally expensive. In practice, many singular models are parametrized by polynomials.…”
Abstract. The accurate asymptotic evaluation of marginal likelihood integrals is a fundamental problem in Bayesian statistics. Following the approach introduced by Watanabe, we translate this into a problem of computational algebraic geometry, namely, to determine the real log canonical threshold of a polynomial ideal, and we present effective methods for solving this problem. Our results are based on resolution of singularities. They apply to parametric models where the Kullback-Leibler distance is upper and lower bounded by scalar multiples of some sum of squared real analytic functions. Such models include finite state discrete models.
“…Thus, we can ignore the origin in computing the RLCT. All other points on the exceptional divisor of this blowup lie on some other chart of the blowup where the pullback pair is (s; s 6 ), so the RLCT is at least (7,1). In the chart where…”
Section: Appendicesmentioning
confidence: 99%
“…While general algorithms exist for monomializing any analytic function [7,4], applying them to nonpolynomial functions such as K(ω) can be computationally expensive. In practice, many singular models are parametrized by polynomials.…”
Abstract. The accurate asymptotic evaluation of marginal likelihood integrals is a fundamental problem in Bayesian statistics. Following the approach introduced by Watanabe, we translate this into a problem of computational algebraic geometry, namely, to determine the real log canonical threshold of a polynomial ideal, and we present effective methods for solving this problem. Our results are based on resolution of singularities. They apply to parametric models where the Kullback-Leibler distance is upper and lower bounded by scalar multiples of some sum of squared real analytic functions. Such models include finite state discrete models.
“…In our case the order has remained constant at the origin, so one has to consider a finer measure. We will not go into detail but with the help of resolution invariants one can detect an improvement of this singularity; for details see [2,3,15]. Now there is just one chart missing, the z-chart.…”
Abstract. The courses are Triviality, Tangency, Transversality, Symmetry, Simplicity, Singularity. These characteristic local plates serve as our invitation to algebraic surfaces and their resolution. Please take a seat.
“…The surfaces live in affine three-space A 3 K = K 3 , where K is a field (of characteristic 0). Mostly we work over the ground field R of real numbers.…”
Abstract. The courses are Triviality, Tangency, Transversality, Symmetry, Simplicity, Singularity. These characteristic local plates serve as our invitation to algebraic surfaces and their resolution. Please take a seat.
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