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On Gromov’s Method of Selecting Heavily Covered Points
, 2013
"... A result of Boros and Füredi (d = 2) and of Bárány (arbitrary d) asserts that for every d there exists cd> 0 such that for every npoint set P ⊂ Rd, some point of Rd is covered by at least cd n d+1 of the dsimplices spanned by the points of P. The largest possible value of cd has been the sub ..."
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Cited by 21 (2 self)
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A result of Boros and Füredi (d = 2) and of Bárány (arbitrary d) asserts that for every d there exists cd> 0 such that for every npoint set P ⊂ Rd, some point of Rd is covered by at least cd n d+1 of the dsimplices spanned by the points of P. The largest possible value of cd has been
Selecting Heavily Covered Points by Pseudocircles, Spheres and Rectangles
, 2002
"... In this paper we prove several pointselection theorems concerning objects "spanned" by a finite set of points. For example, we show that for any set P of n points in R² and any set C of m >= 4n distinct pseudocircles, each passing through a distinct pair of points of P , ther ..."
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In this paper we prove several pointselection theorems concerning objects "spanned" by a finite set of points. For example, we show that for any set P of n points in R² and any set C of m >= 4n distinct pseudocircles, each passing through a distinct pair of points of P
To cite this version: Daniel Král’, Lukás ̌ Mach, JeanSébastien Sereni. A New Lower Bound Based on Gromov’s Method of Selecting Heavily Covered Points. Discrete and Computational Geometry, Springer
, 2013
"... HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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heavily covered points∗ Daniel Král’ † Lukás ̌ Mach ‡ JeanSébastien Sereni§ Boros and Füredi (for d = 2) and Bárány (for arbitrary d) proved that there exists a positive real number cd such that for every set P of n points in R d in general position, there exists a point of Rd contained in at least
A Threshold of ln n for Approximating Set Cover
 JOURNAL OF THE ACM
, 1998
"... Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NPhar ..."
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Cited by 778 (5 self)
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Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NP
Wrappers for Feature Subset Selection
 AIJ SPECIAL ISSUE ON RELEVANCE
, 1997
"... In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set, a ..."
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Cited by 1522 (3 self)
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In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set
Verb Semantics And Lexical Selection
, 1994
"... ... structure. As Levin has addressed (Levin 1985), the decomposition of verbs is proposed for the purposes of accounting for systematic semanticsyntactic correspondences. This results in a series of problems for MT systems: inflexible verb sense definitions; difficulty in handling metaphor and new ..."
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Cited by 520 (4 self)
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and new usages; imprecise lexical selection and insufficient system coverage. It seems one approach is to apply probability methods and statistical models for some of these problems. However, the question reminds: has PSR exhausted the potential of the knowledgebased approach? If not, are there any
A Comparative Study on Feature Selection in Text Categorization
, 1997
"... This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI), ..."
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Cited by 1294 (15 self)
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This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI
An introduction to variable and feature selection
 Journal of Machine Learning Research
, 2003
"... Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. ..."
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Cited by 1283 (16 self)
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Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available.
OPTICS: Ordering Points To Identify the Clustering Structure
, 1999
"... Cluster analysis is a primary method for database mining. It is either used as a standalone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of ..."
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Cited by 511 (49 self)
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.g. representative points, arbitrary shaped clusters), but also the intrinsic clustering structure. For medium sized data sets, the clusterordering can be represented graphically and for very large data sets, we introduce an appropriate visualization technique. Both are suitable for interactive exploration
Results 1  10
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1,765,887