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Mersenne Twister: A 623dimensionally equidistributed uniform pseudorandom number generator
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Reconstruction and Representation of 3D Objects with Radial Basis Functions
 Computer Graphics (SIGGRAPH ’01 Conf. Proc.), pages 67–76. ACM SIGGRAPH
, 2001
"... We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from pointcloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs al ..."
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Cited by 505 (1 self)
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We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from pointcloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs
CATH  a hierarchic classification of protein domain structures
 STRUCTURE
, 1997
"... Background: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structurebased classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function can ..."
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Cited by 470 (33 self)
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can also be assigned. The ever increasing number of known protein structures is too large to classify all proteins manually, therefore, automatic methods are needed for fast evaluation of protein structures. Results: We present a semiautomatic procedure for deriving a novel hierarchical
Bit Commitment Using PseudoRandomness
 Journal of Cryptology
, 1991
"... We show how a pseudorandom generator can provide a bit commitment protocol. We also analyze the number of bits communicated when parties commit to many bits simultaneously, and show that the assumption of the existence of pseudorandom generators suffices to assure amortized O(1) bits of communicat ..."
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Cited by 275 (15 self)
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We show how a pseudorandom generator can provide a bit commitment protocol. We also analyze the number of bits communicated when parties commit to many bits simultaneously, and show that the assumption of the existence of pseudorandom generators suffices to assure amortized O(1) bits
Mining timechanging data streams
 IN PROC. OF THE 2001 ACM SIGKDD INTL. CONF. ON KNOWLEDGE DISCOVERY AND DATA MINING
, 2001
"... Most statistical and machinelearning algorithms assume that the data is a random sample drawn from a stationary distribution. Unfortunately, most of the large databases available for mining today violate this assumption. They were gathered over months or years, and the underlying processes genera ..."
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Cited by 338 (5 self)
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cesses generating them changed during this time, sometimes radically. Although a number of algorithms have been proposed for learning timechanging concepts, they generally do not scale well to very large databases. In this paper we propose an efficient algorithm for mining decision trees from continuously
A statistical test suite for random and pseudorandom number generators for cryptographic applications
, 2001
"... (NIST) promotes the U.S. economy and public welfare by providing technical leadership for the nation’s measurement and standards infrastructure. ITL develops tests, test methods, reference data, proof of concept implementations, and technical analysis to advance the development and productive use of ..."
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Cited by 195 (0 self)
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(NIST) promotes the U.S. economy and public welfare by providing technical leadership for the nation’s measurement and standards infrastructure. ITL develops tests, test methods, reference data, proof of concept implementations, and technical analysis to advance the development and productive use of information technology. ITL’s responsibilities include the development of technical, physical, administrative, and management standards and guidelines for the costeffective security and privacy of sensitive unclassified information in Federal computer systems. This Special Publication 800series reports on ITL’s research, guidance, and outreach efforts in computer security and its collaborative activities with industry, government, and academic organizations. National Institute of Standards and Technology Special Publication 80022 revision 1
Pseudorandom Number Generation: Impossibility and . . .
, 2006
"... Pseudorandom number generators are widely used in the area of simulation. Defective generators are still widely used in standard library programs, although better pseudorandom number generators such as the Mersenne Twister are freely available. This manuscript gives a brief explanation on pseudoran ..."
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on pseudorandom number generators for Monte Carlo simulation. The existing definitions of pseudorandomness are not satisfactorially practical, since the generation of sequences satisfying the definitions is sometimes impossible, somtimes rather slow. As a compromise, to design a fast and reliable generator, some
A progressive refinement approach to fast radiosity image generation
 Computer Graphics
, 1988
"... A reformulated radiosity algorithm is presented that produces initial images in time linear to the number of patches. The enormous memory costs of the radiosity algorithm are also eliminated by computing formfactors onthefly. The technique is based on the approach of rendering by progressive ref ..."
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Cited by 266 (5 self)
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A reformulated radiosity algorithm is presented that produces initial images in time linear to the number of patches. The enormous memory costs of the radiosity algorithm are also eliminated by computing formfactors onthefly. The technique is based on the approach of rendering by progressive
Synthesizing Natural Textures
 In ACM Symposium on Interactive 3D Graphics
"... We present a simple texture synthesis algorithm that is wellsuited for a specific class of naturally occurring textures. This class includes quasirepeating patterns consisting of small objects of familiar but irregular size, such as flower fields, pebbles, forest undergrowth, bushes and tree branc ..."
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Cited by 312 (1 self)
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branches. The algorithm starts from a sample image and generates a new image of arbitrary size the appearance of which is similar to that of the original image. This new image does not change the basic spatial frequencies the original image; instead it creates an image that is a visually similar
On the Fast Generation of Longperiod Pseudorandom Number Sequences
"... AbstractMonte Carlo simulations and other scientific applications that depend on random numbers are increasingly implemented in parallel configurations in programmable hardware. Highquality pseudorandom number generators (PRNGs), such as the Mersenne Twister, are based on binary linear recurrenc ..."
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AbstractMonte Carlo simulations and other scientific applications that depend on random numbers are increasingly implemented in parallel configurations in programmable hardware. Highquality pseudorandom number generators (PRNGs), such as the Mersenne Twister, are based on binary linear
Results 1  10
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