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5,519
Compiler Optimization of Scalar Value Communication Between Speculative Threads
 In Proceedings of the 10th ASPLOS
, 2002
"... While there have been many recent proposals for hardware that supports ThreadLevel Speculation (TLS), there has been relatively little work on compiler optimizations to fully exploit this potential for parallelizing programs optimistically. In this paper, we focus on one important limitation of pro ..."
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Cited by 90 (18 self)
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of program performance under TLS, which is stalls due to forwarding scalar values between threads that would otherwise cause frequent data dependences. We present and evaluate dataflow algorithms for three increasinglyaggressive instruction scheduling techniques that reduce the critical forwarding path
Reliable Verification Using Symbolic Simulation with Scalar Values
 in Proc. DAC, 2000
, 2000
"... This paper presents an algorithm for hardware verification that uses simulation and satisfiability checking techniques to determine the correctness of a symbolic test case on a circuit. The goal is to have coverage greater than that of random testing, but with the ease of use and predictability of d ..."
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Cited by 10 (1 self)
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of directed testing. The user uses symbolic variables in simple directed tests to increase the input space that is explored. The algorithm, which is called quasisymbolic simulation, simulates these tests using only scalar (0,1,X) values internally causing potentially conservative values to be generated
ON SCALARVALUED NONLINEAR ABSOLUTELY SUMMING MAPPINGS
, 2003
"... Abstract. In this note we investigate cases (coincidence situations) in which every scalarvalued continuous nhomogeneous polynomials (nlinear mappings) is absolutely (p; q)summing. We extend some well known coincidence situations and obtain several noncoincidence results, inspired in a linear tech ..."
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Cited by 4 (4 self)
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Abstract. In this note we investigate cases (coincidence situations) in which every scalarvalued continuous nhomogeneous polynomials (nlinear mappings) is absolutely (p; q)summing. We extend some well known coincidence situations and obtain several noncoincidence results, inspired in a linear technique due to Lindenstrauss and Pe̷lczyński. 1.
Simplification of Tetrahedral Meshes by Scalar Value Assignment
, 2002
"... A new approach to simplification of volumetric data over an unstructured tetrahedral mesh is presented. The data consist of sample values of a scalar field defined over a spatial domain, which is subdivided with a tetrahedral mesh. Simplification is performed by means of contraction of the tetrahe ..."
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A new approach to simplification of volumetric data over an unstructured tetrahedral mesh is presented. The data consist of sample values of a scalar field defined over a spatial domain, which is subdivided with a tetrahedral mesh. Simplification is performed by means of contraction
Reliable Verification Using Symbolic Simulation with Scalar Values
 in Proc. DAC, 2000
, 2000
"... This paper presents an algorithm for hardware verification that uses simulation and satisfiability checking techniques to determine the correctness of a symbolic test case on a circuit. The goal is to have coverage greater than that of random testing, but with the ease of use and predictability of d ..."
Abstract
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of directed testing. The user uses symbolic variables in simple directed tests to increase the input space that is explored. The algorithm, which is called quasisymbolic simulation, simulates these tests using only scalar (0,1,X) values internally causing potentially conservative values to be generated
Continuous ScalarValued Multivariable Function Learning for. . .
, 1997
"... : Three neural structures dedicated to continuous function approximation are evaluated and compared with a view to the implementation of an adaptive kinematic approach for visionbased robotic control. This approach is using an iterative method of nonlinear mapping inversion, developed by S. Lee and ..."
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types : Least Mean Squares (LMS) and Total Least Squares (TLS).  CONTINUOUS SCALAR...
Image denoising using a scale mixture of Gaussians in the wavelet domain
 IEEE TRANS IMAGE PROCESSING
, 2003
"... We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vecto ..."
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Cited by 513 (17 self)
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vector and a hidden positive scalar multiplier. The latter modulates the local variance of the coefficients in the neighborhood, and is thus able to account for the empirically observed correlation between the coefficient amplitudes. Under this model, the Bayesian least squares estimate of each
Progressive Meshes
"... Highly detailed geometric models are rapidly becoming commonplace in computer graphics. These models, often represented as complex triangle meshes, challenge rendering performance, transmission bandwidth, and storage capacities. This paper introduces the progressive mesh (PM) representation, a new s ..."
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Cited by 1315 (11 self)
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. In addition, we present a new mesh simplification procedure for constructing a PM representation from an arbitrary mesh. The goal of this optimization procedure is to preserve not just the geometry of the original mesh, but more importantly its overall appearance as defined by its discrete and scalar
The Dantzig selector: statistical estimation when p is much larger than n
, 2005
"... In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Ax + z, where x ∈ R p is a parameter vector of interest, A is a data matrix with possibly far fewer rows than columns, n ≪ ..."
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Cited by 879 (14 self)
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, where r is the residual vector y − A˜x and t is a positive scalar. We show that if A obeys a uniform uncertainty principle (with unitnormed columns) and if the true parameter vector x is sufficiently sparse (which here roughly guarantees that the model is identifiable), then with very large probability
A NOTE ON SCALARVALUED ABSOLUTELY SUMMING HOMOGENEOUS POLYNOMIALS BETWEEN BANACH SPACES
, 2003
"... Abstract. In this note we show that the well known coincidence results for scalarvalued homogeneous polynomials can not be generalized in some natural directions. 1. ..."
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Abstract. In this note we show that the well known coincidence results for scalarvalued homogeneous polynomials can not be generalized in some natural directions. 1.
Results 1  10
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5,519