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Learning Autonomous Navigation Abilities Using Hyper Basis Functions Networks
, 1992
"... A system that learns how to react to visual inputs in order to accomplish simple autonomous navigation tasks is presented. The technique of Hyper Basis Functions Networks along with the use that of it can be made in problems of learning from examples is first outlined, and the various stages of the ..."
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A system that learns how to react to visual inputs in order to accomplish simple autonomous navigation tasks is presented. The technique of Hyper Basis Functions Networks along with the use that of it can be made in problems of learning from examples is first outlined, and the various stages
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 500 (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
A formal basis for architectural connection
 ACM TRANSACTIONS ON SOJIWARE ENGINEERING AND METHODOLOGY
, 1997
"... ..."
EntropyBased Algorithms For Best Basis Selection
 IEEE Transactions on Information Theory
, 1992
"... pretations (position, frequency, and scale), and we have experimented with featureextraction methods that use bestbasis compression for frontend complexity reduction. The method relies heavily on the remarkable orthogonality properties of the new libraries. It is obviously a nonlinear transformat ..."
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Cited by 670 (20 self)
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the class of functionals usable by the method, speeds the bestbasis search, and provides a geom
Sparse coding with an overcomplete basis set: a strategy employed by V1
 Vision Research
, 1997
"... The spatial receptive fields of simple cells in mammalian striate cortex have been reasonably well described physiologically and can be characterized as being localized, oriented, and ban@ass, comparable with the basis functions of wavelet transforms. Previously, we have shown that these receptive f ..."
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Cited by 954 (12 self)
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The spatial receptive fields of simple cells in mammalian striate cortex have been reasonably well described physiologically and can be characterized as being localized, oriented, and ban@ass, comparable with the basis functions of wavelet transforms. Previously, we have shown that these receptive
Regularization Theory and Neural Networks Architectures
 Neural Computation
, 1995
"... We had previously shown that regularization principles lead to approximation schemes which are equivalent to networks with one layer of hidden units, called Regularization Networks. In particular, standard smoothness functionals lead to a subclass of regularization networks, the well known Radial Ba ..."
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Cited by 396 (33 self)
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to different classes of basis functions. Additive splines as well as some tensor product splines can be obtained from appropriate classes of smoothness functionals. Furthermore, the same generalization that extends Radial Basis Functions (RBF) to Hyper Basis Functions (HBF) also leads from additive models
Monads for functional programming
, 1995
"... The use of monads to structure functional programs is described. Monads provide a convenient framework for simulating effects found in other languages, such as global state, exception handling, output, or nondeterminism. Three case studies are looked at in detail: how monads ease the modification o ..."
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Cited by 1481 (39 self)
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The use of monads to structure functional programs is described. Monads provide a convenient framework for simulating effects found in other languages, such as global state, exception handling, output, or nondeterminism. Three case studies are looked at in detail: how monads ease the modification
Greedy Function Approximation: A Gradient Boosting Machine
 Annals of Statistics
, 2000
"... Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed for additi ..."
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Cited by 951 (12 self)
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Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed
Short signatures from the Weil pairing
, 2001
"... Abstract. We introduce a short signature scheme based on the Computational DiffieHellman assumption on certain elliptic and hyperelliptic curves. The signature length is half the size of a DSA signature for a similar level of security. Our short signature scheme is designed for systems where signa ..."
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Cited by 743 (28 self)
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Abstract. We introduce a short signature scheme based on the Computational DiffieHellman assumption on certain elliptic and hyperelliptic curves. The signature length is half the size of a DSA signature for a similar level of security. Our short signature scheme is designed for systems where
Functional discovery via a compendium of expression profiles. Cell 102:109
, 2000
"... have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of ..."
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Cited by 537 (8 self)
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have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of
Results 1  10
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2,582,675