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large numbers in

by Masayuki Kumon, Akimichi Takemura , 2005
"... a simple strategy weakly forcing the strong law of ..."
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a simple strategy weakly forcing the strong law of

with large numbers

by M. P. Enright, L. Huyse, R. C. Mcclung
"... mechanics-based probabilistic life prediction of components ..."
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mechanics-based probabilistic life prediction of components

Determining the Number of Factors in Approximate Factor Models

by Jushan Bai, Serena Ng , 2000
"... In this paper we develop some statistical theory for factor models of large dimensions. The focus is the determination of the number of factors, which is an unresolved issue in the rapidly growing literature on multifactor models. We propose a panel Cp criterion and show that the number of factors c ..."
Abstract - Cited by 561 (30 self) - Add to MetaCart
In this paper we develop some statistical theory for factor models of large dimensions. The focus is the determination of the number of factors, which is an unresolved issue in the rapidly growing literature on multifactor models. We propose a panel Cp criterion and show that the number of factors

SCRIBE: A large-scale and decentralized application-level multicast infrastructure

by Miguel Castro, Peter Druschel, Anne-Marie Kermarrec, Antony Rowstron - IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (JSAC , 2002
"... This paper presents Scribe, a scalable application-level multicast infrastructure. Scribe supports large numbers of groups, with a potentially large number of members per group. Scribe is built on top of Pastry, a generic peer-to-peer object location and routing substrate overlayed on the Internet, ..."
Abstract - Cited by 658 (29 self) - Add to MetaCart
This paper presents Scribe, a scalable application-level multicast infrastructure. Scribe supports large numbers of groups, with a potentially large number of members per group. Scribe is built on top of Pastry, a generic peer-to-peer object location and routing substrate overlayed on the Internet

Large Numbers in Computing and

by Hazel Atkins, Rebecca Coates, Sophie Hilditch
"... We present an overview of large numbers within mathematics and computing. Particular emphasis is put on the problem of large number notation in the mathematical attempt to get closer to infinity. ..."
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We present an overview of large numbers within mathematics and computing. Particular emphasis is put on the problem of large number notation in the mathematical attempt to get closer to infinity.

Large steps in cloth simulation

by David Baraff, Andrew Witkin - SIGGRAPH 98 Conference Proceedings , 1998
"... The bottle-neck in most cloth simulation systems is that time steps must be small to avoid numerical instability. This paper describes a cloth simulation system that can stably take large time steps. The simulation system couples a new technique for enforcing constraints on individual cloth particle ..."
Abstract - Cited by 576 (5 self) - Add to MetaCart
as well. The implicit integration method generates a large, unbanded sparse linear system at each time step which is solved using a modified conjugate gradient method that simultaneously enforces particles ’ constraints. The constraints are always maintained exactly, independent of the number of conjugate

Forecasting using principal components from a large number of predictors

by James H. Stock, Mark W. Watson - Journal of the American Statistical Association
"... This article considers forecasting a single time series when there are many predictors (N) and time series observations (T). When the data follow an approximate factor model, the predictors can be summarized by a small number of indexes, which we estimate using principal components. Feasible forecas ..."
Abstract - Cited by 233 (5 self) - Add to MetaCart
in the presence of time variation in the factor model. KEY WORDS: Factor models; Forecasting; Principal components. This article considers forecasting one series using a large number of predictor series. In macroeconomic forecasting, for example, the number of candidate predictor series (N) can be very large

CURE: An Efficient Clustering Algorithm for Large Data sets

by Sudipto Guha, Rajeev Rastogi, Kyuseok Shim - Published in the Proceedings of the ACM SIGMOD Conference , 1998
"... Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new clustering ..."
Abstract - Cited by 722 (5 self) - Add to MetaCart
clustering algorithm called CURE that is more robust to outliers, and identifies clusters having non-spherical shapes and wide variances in size. CURE achieves this by representing each cluster by a certain fixed number of points that are generated by selecting well scattered points from the cluster

Large margin methods for structured and interdependent output variables

by Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun - JOURNAL OF MACHINE LEARNING RESEARCH , 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
Abstract - Cited by 624 (12 self) - Add to MetaCart
to accomplish this, we propose to appropriately generalize the well-known notion of a separation margin and derive a corresponding maximum-margin formulation. While this leads to a quadratic program with a potentially prohibitive, i.e. exponential, number of constraints, we present a cutting plane algorithm

New Look at the Large Numbers

by Thomas Görnitz - Int. J. Theor. Phys , 1986
"... A new interpretation for the large number hypothesis is given, referring to the close connection between the Bekenstein-Hawking entropy and Weizsäckers ur theory. 1. ..."
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A new interpretation for the large number hypothesis is given, referring to the close connection between the Bekenstein-Hawking entropy and Weizsäckers ur theory. 1.
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