geometric quotient

  • 121Errors and residuals in statistics — For other senses of the word residual , see Residual. In statistics and optimization, statistical errors and residuals are two closely related and easily confused measures of the deviation of a sample from its theoretical value . The error of a… …

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  • 122Whitehead torsion — In mathematics, Whitehead torsion is an invariant of an h cobordism in a Whitehead group, that is important in simple homotopy theory and surgery theory. It is named for J. H. C. Whitehead.Whitehead torsionSuppose that W is an h cobordism from M… …

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  • 123Algebraic stack — In algebraic geometry, an algebraic stack is a concept introduced to generalize algebraic varieties, schemes, and algebraic spaces. They were originally proposed in a 1969 paper[1] by Pierre Deligne and David Mumford to define the (fine) moduli… …

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  • 124Spherical 3-manifold — In mathematics, a spherical 3 manifold M is a 3 manifold of the form M = S3 / Γ where Γ is a finite subgroup of SO(4) acting freely by rotations on the 3 sphere S3. All such manifolds are prime, orientable, and closed. Spherical 3 manifolds are… …

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  • 125Symplectic cut — In mathematics, specifically in symplectic geometry, the symplectic cut is a geometric modification on symplectic manifolds. Its effect is to decompose a given manifold into two pieces. There is an inverse operation, the symplectic sum, that… …

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  • 126Lattice (discrete subgroup) — In Lie theory and related areas of mathematics, a lattice in a locally compact topological group is a discrete subgroup with the property that the quotient space has finite invariant measure. In the special case of subgroups of R n , this amounts …

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  • 127Bogomolov–Miyaoka–Yau inequality — In mathematics, the Bogomolov–Miyaoka–Yau inequality is the inequality between Chern numbers of compact complex surfaces of general type. Its major interest is the way it restricts the possible topological types of the underlying real 4 manifold …

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  • 128Principal components analysis — Principal component analysis (PCA) is a vector space transform often used to reduce multidimensional data sets to lower dimensions for analysis. Depending on the field of application, it is also named the discrete Karhunen Loève transform (KLT),… …

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