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On iterated forcing for successors of regular cardinals
 Fundamenta Mathematicae
"... Abstract. We investigate the problem of when ≤ λ–support iterations of < λ–complete notions of forcing preserve λ +. We isolate a property — properness over diamonds — that implies λ + is preserved and show that this property is preserved by λ–support iterations. Our condition is a relative of th ..."
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cardinal satisfying λ = λ <λ. • D is a normal filter on λ “with diamonds”, i.e., for every S ∈ D +, there is a sequence 〈Aδ: δ ∈ S 〉 such that for every A ⊆ λ, {δ ∈ S: A ∩ δ = Aδ} ∈ D +. • χ is a regular cardinal that is “large enough”. We are going to be looking at when λ + is preserved by (≤)λ
Identifying high cardinality internet hosts
 In Proceedings of IEEE INFOCOM
, 2009
"... Abstract—The Internet host cardinality, defined as the number of distinct peers that an Internet host communicates with, is an important metric for profiling Internet hosts. Some example applications include behavior based network intrusion detection, p2p hosts identification, and server identificat ..."
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cardinalities. These methods do not work well with hosts of moderately large cardinalities that are needed for certain host behavior profiling such as detection of p2p hosts or port scanners. In this paper, we propose an online sampling approach for identifying hosts whose cardinality exceeds some moderate
PRECIPITOUS TOWERS OF NORMAL FILTERS
, 1995
"... Abstract. We prove that every tower of normal filters of height δ (δ supercompact) is precipitous assuming that each normal filter in the tower is the club filter restricted to a stationary set. We give an example to show that this assumption is necessary. We also prove that every normal filter can ..."
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be generically extended to a wellfounded Vultrafilter (assuming large cardinals). In this paper we investigate towers of normal filters. These towers were first used by Woodin in [W88]. Woodin proved that if δ is a Woodin cardinal and P is the full stationary tower up to δ (P<δ) or the countable version (Q
Multidimensional Filter Networks Mats Andesson ∗ Oleg Burdakov†
, 2014
"... Abstract Filter networks are used as a powerful tool used for reducing the image processing time and maintaining high image quality. They are composed of sparse subfilters whose high sparsity ensures fast image processing. The filter network design is related to solving a sparse optimization proble ..."
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problem where a cardinality constraint bounds above the sparsity level. In the case of sequentially connected subfilters, which is the simplest network structure of those considered in this paper, a cardinalityconstrained multilinear leastsquares (MLLS) problem is to be solved. Even when disregarding
Multidimensional Filter Networks Mats Andesson ∗ Oleg Burdakov †
"... Abstract Filter networks is a powerful tool used for reducing the image processing time, while maintaining its reasonably high quality. They are composed of sparse subfilters whose low sparsity ensures fast image processing. The filter network design is related to solving a sparse optimization probl ..."
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problem where a cardinality constraint bounds above the sparsity level. In the case of sequentially connected subfilters, which is the simplest network structure of those considered in this paper, a cardinalityconstrained multilinear leastsquares (MLLS) problem is to be solved. If to disregard
ABSTRACT Tracking Multiple Speakers Using CPHD Filter
"... In this paper, we present an efficient method for tracking multiple speakers in a reverberant environment. The proposed method is based on the cardinalized probability hypothesis density (CPHD) filter. Because the CPHD filter can handle a large amount of clutter measurements, our method has a high r ..."
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In this paper, we present an efficient method for tracking multiple speakers in a reverberant environment. The proposed method is based on the cardinalized probability hypothesis density (CPHD) filter. Because the CPHD filter can handle a large amount of clutter measurements, our method has a high
SMALL uκ AND LARGE 2 κ FOR SUPERCOMPACT κ
"... Abstract. Garti and Shelah [2] state that one can force uκ to be κ+ for supercompact κ with 2κ arbitrarily large, using the technique of Džamonja and Shelah [1]. Here we spell out how this can be done. §1. Introduction. For any regular cardinal λ, we let uλ = min{B  : B is a filter base for a un ..."
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Abstract. Garti and Shelah [2] state that one can force uκ to be κ+ for supercompact κ with 2κ arbitrarily large, using the technique of Džamonja and Shelah [1]. Here we spell out how this can be done. §1. Introduction. For any regular cardinal λ, we let uλ = min{B  : B is a filter base for a
Gap forcing: generalizing the Lévy–Solovay theorem
 Bull. Symb. Log
, 1999
"... Abstract. The LevySolovay Theorem [LevSol67] limits the kind of large cardinal embeddings that can exist in a small forcing extension. Here I announce a generalization of this theorem to a broad new class of forcing notions. One consequence is that many of the forcing iterations most commonly found ..."
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Abstract. The LevySolovay Theorem [LevSol67] limits the kind of large cardinal embeddings that can exist in a small forcing extension. Here I announce a generalization of this theorem to a broad new class of forcing notions. One consequence is that many of the forcing iterations most commonly
Possible Size of an Ultrapower of ω 1
"... Let ω be the first infinite ordinal (or the set of all natural numbers) with the usual order <. In §1 we show that, assuming the consistency of a supercompact cardinal, there may exist an ultrapower of ω, whose cardinality is (1) a singular strong limit cardinal, (2) a strongly inaccessible cardi ..."
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cardinal. This answers two questions in [1], modulo the assumption of supercompactness. In §2 we construct several λArchimedean ultrapowers of ω under some large cardinal assumptions. For example, we show that, assuming the consistency of a measurable cardinal, there may exist a λArchimedean ultrapower
On Matrices, Automata, and Double Counting in Constraint Programming
 CONSTRAINTS
"... Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables M, with the same constraint C defined by a finitestate automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting, ..."
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Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables M, with the same constraint C defined by a finitestate automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting
Results 1  10
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55