نتایج جستجو برای: locally segment dense set

تعداد نتایج: 863672  

Journal: :Proceedings of the American Mathematical Society 2000

2003
Mai Gehrke Carol Walker Elbert Walker

Stone algebras have been characterized by Chen and Grätzer in terms of triples (B;D;'), whereD is a distributive lattice with 1; B is a Boolean algebra, and ' is a bounded lattice homomorphism from B into the lattice of …lters of D: If D is bounded, the construction of these characterizing triples is much simpler, since the homomorphism ' can be replaced by one from B into D itself. The triple ...

Journal: :CoRR 2016
Pavel Dvorák Dusan Knop Tomás Toufar

In this paper we study the Target Set Selection problem, a fundamental problem in computational social choice, from a parameterized complexity perspective. Here for a given graph and a threshold for each vertex the task is to find a set of active vertices that activates whole graph. A vertex becomes active if the number of activated vertices in its neighborhood is at least its threshold. We giv...

2002
MAXWELL B. STINCHCOMBE

Many nonparametric estimators and tests are naturally set in infinite dimensional contexts. Prevalence is the infinite dimensional analogue of full Lebesgue measure, shyness the analogue of being a Lebesgue null set. A prevalent set of prior distributions lead to wildly inconsistent Bayesian updating when independent and identically distributed observations happen in class of infinite spaces th...

Journal: :Mathematische Nachrichten 2022

We establish the notion of a ``projective analytic vector'', whose defining requirements are weaker than usual ones an vector, and use it to prove generation theorems for one-parameter groups on locally convex spaces. More specifically, we give characterization generators strongly continuous which arise as result projective limit procedure, in existence dense set vectors plays central role. An ...

2014
Guru Guruganesh

The unique games conjecture has been a very influential conjecture with many striking and profound implications. Originally proposed by Khot [Kho02], a positive resolution to the conjecture, would imply that many natural and important questions can be approximated by a basic SDP algorithm (see [Rag08]) and that no algorithm can do better (unless P = NP ). Many important practical problems such ...

Journal: :Sig. Proc.: Image Comm. 2007
Michael Bleyer Margrit Gelautz

This paper describes a dense stereo matching algorithm for epipolar rectified images. The method applies colour segmentation on the reference image. Our basic assumptions are that disparity varies smoothly inside a segment, while disparity boundaries coincide with the segment borders. The use of these assumptions makes the algorithm capable of handling large untextured regions, estimating preci...

Journal: :Topology and its Applications 2022

Let X be a Hausdorff quotient of standard space (that is locally compact separable metric space). It shown that the following are equivalent: (i) image an irreducible map from space; (ii) has sequentially dense subset satisfying two technical conditions involving double sequences; (iii) whenever q : Y → , restriction ⁎ | V onto (where pure derived and closure set singleton fibres ). The proof u...

2003
W. W. Comfort Sidney A. Morris

A subset S of a topological group G is said to be a suitable set if (a) it has the discrete topology, (b) it is a closed subset of G \ {l}, and (c) the subgroup generated by S is dense in G. K.H. Hoffmann and S.A. Morris proved that every locally compact group has a suitable set. In this paper it is proved that every metrizable topological group and every countable Hausdorff topological group h...

2012
Yinsong Pan Junyuan Wu Hong Huang Jiamin Liu

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computa...

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