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Simplex Range Reporting on a Pointer Machine
"... Abstract We give a lower bound on the following problem, known as simplex range reporting: Given a collection P of n points in dspace and an arbitrary simplex q, find all the points in P " q. It is understood that P is fixed and can be preprocessed ahead of time, while q is a query that mu ..."
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Abstract We give a lower bound on the following problem, known as simplex range reporting: Given a collection P of n points in dspace and an arbitrary simplex q, find all the points in P " q. It is understood that P is fixed and can be preprocessed ahead of time, while q is a query
Lower Bounds on the Complexity of Simplex Range Reporting on a Pointer Machine (Extended Abstract)
, 1992
"... We give a lower bound on the following problem, known as simplex range reporting: Given a collection P of n points in dspace and an arbitrary simplex q, find all the points in P " q. It is understood that P is fixed and can be preprocessed ahead of time, while q is a query that must be an ..."
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Cited by 14 (1 self)
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We give a lower bound on the following problem, known as simplex range reporting: Given a collection P of n points in dspace and an arbitrary simplex q, find all the points in P " q. It is understood that P is fixed and can be preprocessed ahead of time, while q is a query that must
Sketchpad: A manmachine graphical communication system
, 2003
"... The Sketchpad system uses drawing as a novel communication medium for a computer. The system contains input, output, and computation programs which enable it to interpret information drawn directly on a computer display. It has been used to draw electrical, mechanical, scientific, mathematical, and ..."
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Cited by 702 (6 self)
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The Sketchpad system uses drawing as a novel communication medium for a computer. The system contains input, output, and computation programs which enable it to interpret information drawn directly on a computer display. It has been used to draw electrical, mechanical, scientific, mathematical
A learning algorithm for Boltzmann machines
 Cognitive Science
, 1985
"... The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a probl ..."
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Cited by 586 (13 self)
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The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a
Fast Parallel Algorithms for ShortRange Molecular Dynamics
 JOURNAL OF COMPUTATIONAL PHYSICS
, 1995
"... Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of interatomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dyn ..."
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Cited by 622 (6 self)
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. The algorithms are tested on a standard LennardJones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers  the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray YMP and C90 algorithm shows
Machine Learning in Automated Text Categorization
 ACM COMPUTING SURVEYS
, 2002
"... The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this p ..."
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Cited by 1658 (22 self)
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to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual
Efficient ContextSensitive Pointer Analysis for C Programs
, 1995
"... This paper proposes an efficient technique for contextsensitive pointer analysis that is applicable to real C programs. For efficiency, we summarize the effects of procedures using partial transfer functions. A partial transfer function (PTF) describes the behavior of a procedure assuming that certa ..."
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Cited by 435 (7 self)
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This paper proposes an efficient technique for contextsensitive pointer analysis that is applicable to real C programs. For efficiency, we summarize the effects of procedures using partial transfer functions. A partial transfer function (PTF) describes the behavior of a procedure assuming
BLEU: a Method for Automatic Evaluation of Machine Translation
, 2002
"... Human evaluations of machine translation are extensive but expensive. Human evaluations can take months to finish and involve human labor that can not be reused. ..."
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Cited by 2107 (4 self)
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Human evaluations of machine translation are extensive but expensive. Human evaluations can take months to finish and involve human labor that can not be reused.
MatÃ©: A Tiny Virtual Machine for Sensor Networks
, 2002
"... Composed of tens of thousands of tiny devices with very limited resources ("motes"), sensor networks are subject to novel systems problems and constraints. The large number of motes in a sensor network means that there will often be some failing nodes; networks must be easy to repopulate. ..."
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Cited by 502 (21 self)
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late. Often there is no feasible method to recharge motes, so energy is a precious resource. Once deployed, a network must be reprogrammable although physically unreachable, and this reprogramming can be a significant energy cost. We present MatÃ©, a tiny communicationcentric virtual machine designed
Sparse Bayesian Learning and the Relevance Vector Machine
, 2001
"... This paper introduces a general Bayesian framework for obtaining sparse solutions to regression and classication tasks utilising models linear in the parameters. Although this framework is fully general, we illustrate our approach with a particular specialisation that we denote the `relevance vec ..."
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Cited by 958 (5 self)
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vector machine' (RVM), a model of identical functional form to the popular and stateoftheart `support vector machine' (SVM). We demonstrate that by exploiting a probabilistic Bayesian learning framework, we can derive accurate prediction models which typically utilise dramatically fewer
Results 1  10
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713,937