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High dimensional graphs and variable selection with the Lasso

by Nicolai Meinshausen, Peter Bühlmann - ANNALS OF STATISTICS , 2006
"... The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso is a ..."
Abstract - Cited by 736 (22 self) - Add to MetaCart
The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso

Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments

by Gerard Talavera, Jose Castresana - SYST BIOL , 2007
"... Alignment quality may have as much impact on phylogenetic reconstruction as the phylogenetic methods used. Not only the alignment algorithm, but also the method used to deal with the most problematic alignment regions, may have a critical effect on the final tree. Although some authors remove such ..."
Abstract - Cited by 319 (1 self) - Add to MetaCart
in the selection of blocks. Alignments constructed with different alignment methods (ClustalW, Mafft, and Probcons) were used to estimate phylogenetic trees by maximum likelihood, neighbor joining, and parsimony. We show that, in most alignment conditions, and for alignments that are not too short, removal

Tracking join and self-join sizes in limited storage

by Noga Alon, Phillip B. Gibbons, Yossi Matias, Mario Szegedy , 2002
"... This paper presents algorithms for tracking (approximate) join and self-join sizes in limited storage, in the presence of insertions and deletions to the data set(s). Such algorithms detect changes in join and self-join sizes without an expensive recomputation from the base data, and without the lar ..."
Abstract - Cited by 123 (0 self) - Add to MetaCart
the large space overhead required to maintain such sizes exactly. Query optimizers rely on fast, high-quality estimates of join sizes in order to select between various join plans, and estimates of self-join sizes are used to indicate the degree of skew in the data. For self-joins, we considertwo approaches

Selectivity estimation for spatial joins

by Ning An, Zhen-yu Yang, Anand Sivasubramaniam - IEEE ICDE , 2001
"... Spatial Joins are important and time consuming operations in spatial database management systems. It is crucial to be able to accurately estimate the performance of these operations so that one can derive efficient query execution plans, and even develop/refine data structures to improve their perfo ..."
Abstract - Cited by 14 (0 self) - Add to MetaCart
their performance. While estimation techniques for analyzing the performance of other operations, such as range queries, on spatial data has come under scrutiny, the problem of estimating selectivity for spatial joins has been little explored. The limited forays into this area have used parametric techniques, which

Estimating the Selectivity of Spatial Queries Using the `Correlation' Fractal Dimension

by Alberto Belussi, Christos Faloutsos , 1995
"... We examine the estimation of selectivities for range and spatial join queries in real spatial databases. As we have shown earlier [FK94a], real point sets: (a) violate consistently the "uniformity" and "independence" assumptions, (b) can often be described as "fractals" ..."
Abstract - Cited by 125 (18 self) - Add to MetaCart
We examine the estimation of selectivities for range and spatial join queries in real spatial databases. As we have shown earlier [FK94a], real point sets: (a) violate consistently the "uniformity" and "independence" assumptions, (b) can often be described as "

Selectivity Estimation using Probabilistic Models

by Lise Getoor, Ben Taskar, Daphne Koller , 2001
"... Estimating the result size of complex queries that involve selection on multiple attributes and the join of several relations is a difficult but fundamental task in database query processing. It arises in cost-based query optimization, query profiling, and approximate query answering. In this paper, ..."
Abstract - Cited by 98 (3 self) - Add to MetaCart
Estimating the result size of complex queries that involve selection on multiple attributes and the join of several relations is a difficult but fundamental task in database query processing. It arises in cost-based query optimization, query profiling, and approximate query answering. In this paper

On the Estimation of Join Result Sizes

by Arun Swami , K. Bernhard Schiefer , 2006
"... Good estimates of join result sizes are critical for query op-timization in relational database management systems. We address the problem of incrementally obtaining accurate and consistent estimates of join result sizes. We have invented a new rule for choosing join selectiv-ities for estimating j ..."
Abstract - Cited by 21 (0 self) - Add to MetaCart
Good estimates of join result sizes are critical for query op-timization in relational database management systems. We address the problem of incrementally obtaining accurate and consistent estimates of join result sizes. We have invented a new rule for choosing join selectiv-ities for estimating

Selectivity estimation for spatial joins with geometric selections

by Chengyu Sun, Divyakant Agrawal, Amr El Abbadi - In Extending Database Technology , 2002
"... Abstract. Spatial join is an expensive operation that is commonly used in spatial database systems. In order to generate efficient query plans for the queries involving spatial join operations, it is crucial to obtain accurate selectivity estimates for these operations. In this paper we introduce a ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
Abstract. Spatial join is an expensive operation that is commonly used in spatial database systems. In order to generate efficient query plans for the queries involving spatial join operations, it is crucial to obtain accurate selectivity estimates for these operations. In this paper we introduce a

Scalable join processing on very large rdf graphs

by Thomas Neumann, Gerhard Weikum - In SIGMOD Conference , 2009
"... With the proliferation of the RDF data format, engines for RDF query processing are faced with very large graphs that contain hundreds of millions of RDF triples. This paper addresses the resulting scalability problems. Recent prior work along these lines has focused on indexing and other physical-d ..."
Abstract - Cited by 84 (5 self) - Add to MetaCart
for sideways in-formation passing between separate joins at query run-time, to provide highly effective filters on the input streams of joins. Second, we improve previously proposed algorithms for join-order optimization by more accurate selectivity esti-mations for very large RDF graphs. Experimental studies

Hoeffding Inequalities for Join-Selectivity Estimation and Online Aggregation

by Peter J. Haas, Peter J. Haas - IBM Research Report RJ 10040, IBM Almaden Research , 1996
"... This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM ..."
Abstract - Cited by 13 (6 self) - Add to MetaCart
This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and speci c requests. After outside publication, requests should be lled only by reprints or legally obtained copies of the article (e.g., payment of royalties).
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