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Approximating discrete probability distributions with dependence trees

by C. K. Chow, C. N. Liu - IEEE TRANSACTIONS ON INFORMATION THEORY , 1968
"... A method is presented to approximate optimally an n-dimensional discrete probability distribution by a product of second-order distributions, or the distribution of the first-order tree dependence. The problem is to find an optimum set of n-1 first order dependence relationship among the n variables ..."
Abstract - Cited by 881 (0 self) - Add to MetaCart
A method is presented to approximate optimally an n-dimensional discrete probability distribution by a product of second-order distributions, or the distribution of the first-order tree dependence. The problem is to find an optimum set of n-1 first order dependence relationship among the n

Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks

by J. Nicholas Laneman, Gregory W. Wornell - IEEE TRANS. INF. THEORY , 2003
"... We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a m ..."
Abstract - Cited by 622 (5 self) - Add to MetaCart
We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a

Consistent hashing and random trees: Distributed caching protocols for relieving hot spots on the World Wide Web

by David Karger, Eric Lehman, Tom Leighton, Matthew Levine, Daniel Lewin, Rina Panigrahy - IN PROC. 29TH ACM SYMPOSIUM ON THEORY OF COMPUTING (STOC , 1997
"... We describe a family of caching protocols for distrib-uted networks that can be used to decrease or eliminate the occurrence of hot spots in the network. Our protocols are particularly designed for use with very large networks such as the Internet, where delays caused by hot spots can be severe, and ..."
Abstract - Cited by 699 (10 self) - Add to MetaCart
We describe a family of caching protocols for distrib-uted networks that can be used to decrease or eliminate the occurrence of hot spots in the network. Our protocols are particularly designed for use with very large networks such as the Internet, where delays caused by hot spots can be severe

An experimental comparison of three methods for constructing ensembles of decision trees

by Thomas G. Dietterich, Doug Fisher - Bagging, boosting, and randomization. Machine Learning , 2000
"... Abstract. Bagging and boosting are methods that generate a diverse ensemble of classifiers by manipulating the training data given to a “base ” learning algorithm. Breiman has pointed out that they rely for their effectiveness on the instability of the base learning algorithm. An alternative approac ..."
Abstract - Cited by 610 (6 self) - Add to MetaCart
Abstract. Bagging and boosting are methods that generate a diverse ensemble of classifiers by manipulating the training data given to a “base ” learning algorithm. Breiman has pointed out that they rely for their effectiveness on the instability of the base learning algorithm. An alternative

Cooperative diversity in wireless networks: efficient protocols and outage behavior

by J. Nicholas Laneman, David N. C. Tse, Gregory W. Wornell - IEEE TRANS. INFORM. THEORY , 2004
"... We develop and analyze low-complexity cooperative diversity protocols that combat fading induced by multipath propagation in wireless networks. The underlying techniques exploit space diversity available through cooperating terminals’ relaying signals for one another. We outline several strategies ..."
Abstract - Cited by 2009 (31 self) - Add to MetaCart
protocols are efficient in the sense that they achieve full diversity (i.e., second-order diversity in the case of two terminals), and, moreover, are close to optimum (within 1.5 dB) in certain regimes. Thus, using distributed antennas, we can provide the powerful benefits of space diversity without need

Monopolistic competition and optimum product diversity. The American Economic Review,

by Avinash K Dixit , Joseph E Stiglitz , Harold Hotelling , Nicholas Stern , Kelvin Lancaster , Stiglitz , 1977
"... The basic issue concerning production in welfare economics is whether a market solution will yield the socially optimum kinds and quantities of commodities. It is well known that problems can arise for three broad reasons: distributive justice; external effects; and scale economies. This paper is c ..."
Abstract - Cited by 1911 (5 self) - Add to MetaCart
The basic issue concerning production in welfare economics is whether a market solution will yield the socially optimum kinds and quantities of commodities. It is well known that problems can arise for three broad reasons: distributive justice; external effects; and scale economies. This paper

Grid Information Services for Distributed Resource Sharing

by Karl Czajkowski , Steven Fitzgerald, Ian Foster, Carl Kesselman , 2001
"... Grid technologies enable large-scale sharing of resources within formal or informal consortia of individuals and/or institutions: what are sometimes called virtual organizations. In these settings, the discovery, characterization, and monitoring of resources, services, and computations are challengi ..."
Abstract - Cited by 712 (52 self) - Add to MetaCart
are challenging problems due to the considerable diversity, large numbers, dynamic behavior, and geographical distribution of the entities in which a user might be interested. Consequently, information services are a vital part of any Grid software infrastructure, providing fundamental mechanisms for discovery

Locality-sensitive hashing scheme based on p-stable distributions

by Mayur Datar, Piotr Indyk - In SCG ’04: Proceedings of the twentieth annual symposium on Computational geometry , 2004
"... inÇÐÓ�Ò We present a novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem underÐÔnorm, based onÔstable distributions. Our scheme improves the running time of the earlier algorithm for the case of theÐnorm. It also yields the first known provably efficient approximate ..."
Abstract - Cited by 521 (8 self) - Add to MetaCart
inÇÐÓ�Ò We present a novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem underÐÔnorm, based onÔstable distributions. Our scheme improves the running time of the earlier algorithm for the case of theÐnorm. It also yields the first known provably efficient approximate

Pastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems

by Antony Rowstron, Peter Druschel , 2001
"... This paper presents the design and evaluation of Pastry, a scalable, distributed object location and routing scheme for wide-area peer-to-peer applications. Pastry provides application-level routing and object location in a potentially very large overlay network of nodes connected via the Internet. ..."
Abstract - Cited by 2075 (49 self) - Add to MetaCart
This paper presents the design and evaluation of Pastry, a scalable, distributed object location and routing scheme for wide-area peer-to-peer applications. Pastry provides application-level routing and object location in a potentially very large overlay network of nodes connected via the Internet

Random forests

by Leo Breiman, E. Schapire - Machine Learning , 2001
"... Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the fo ..."
Abstract - Cited by 3613 (2 self) - Add to MetaCart
Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees
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