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3,955
Typesetting Concrete Mathematics
 TUGBOAT
, 1989
"... ... tried my best to make the book mathematically interesting, but I also knew that it would be typographically interestingbecause it would be the first major use of a new typeface by Hermann Zapf, commissioned by the American Mathematical Society. This typeface, called AMS Euler, had been carefull ..."
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Cited by 661 (1 self)
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. The underlying philosophy of Zapf's Euler design was to capture the flavor of mathematics as it might be written by a mathematician with excellent handwriting. For example, one of the earmarks of AMS Euler is its zero, 'O', which is slightly pointed at the top because a handwritten zero rarely
Hierarchical Modelling and Analysis for Spatial Data. Chapman and Hall/CRC,
, 2004
"... Abstract Often, there are two streams in statistical research one developed by practitioners and other by main stream statisticians. Development of geostatistics is a very good example where pioneering work under realistic assumptions came from mining engineers whereas it is only now that statisti ..."
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Cited by 442 (45 self)
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Abstract Often, there are two streams in statistical research one developed by practitioners and other by main stream statisticians. Development of geostatistics is a very good example where pioneering work under realistic assumptions came from mining engineers whereas it is only now
Avenues of Spatially Explicit Population Dynamics Modeling — A par excellence Example for Mathematical Heterogeneity in Ecological Models?
"... Abstract: This contribution discusses different approaches to spatially explicit modeling of population dynamics of the intrusion of nonendemic species into patched habitats. Different modeling approaches such as cellular automata, partial differential equations and hybrid Petri nets are summarized ..."
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Abstract: This contribution discusses different approaches to spatially explicit modeling of population dynamics of the intrusion of nonendemic species into patched habitats. Different modeling approaches such as cellular automata, partial differential equations and hybrid Petri nets are summarized. An application of a meta–population model for the Galapagos archipelago is described using a partial differential equation and a Petri net model. A detailed comparison of both models in terms of simulation results and methodology shows how different building blocks of ecological models can be. And the question is raised, how far the integration of models is at all possible and should be aimed at. Results of the investigation give a detailed insight into the problem of scaling ecological models and the core question of what processes should be considered in which scale in terms of space, time or complexity.
Svmknn: Discriminative nearest neighbor classification for visual category recognition
 in CVPR
, 2006
"... We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is quite flexible, and permits recognition based on color, texture, and particularly shape, in a homogeneous framework. While n ..."
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Cited by 342 (10 self)
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We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is quite flexible, and permits recognition based on color, texture, and particularly shape, in a homogeneous framework. While
Pyramidal parametrics
 Computer Graphics (SIGGRAPH ’83 Proceedings
, 1983
"... The mapping of images onto surfaces may substantially increase the realism and information content of computergenerated imagery. The projection of a flat source image onto a curved surface may involve sampling difficulties, however, which are compounded as the view of the surface changes. As the pr ..."
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Cited by 304 (1 self)
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; prefiltering and sampling geometry which minimizes aliasing effects and assures continuity within and between target images. Although the mapping of texture onto surfaces is an excellent example of the process and provided the original motivation for its development, pyramidal parametric data structures admit
A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features
 Machine Learning
, 1993
"... In the past, nearest neighbor algorithms for learning from examples have worked best in domains in which all features had numeric values. In such domains, the examples can be treated as points and distance metrics can use standard definitions. In symbolic domains, a more sophisticated treatment of t ..."
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Cited by 309 (3 self)
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In the past, nearest neighbor algorithms for learning from examples have worked best in domains in which all features had numeric values. In such domains, the examples can be treated as points and distance metrics can use standard definitions. In symbolic domains, a more sophisticated treatment
A new meshless local PetrovGalerkin (MLPG) approach in computational mechanics
 Comput. Mech
, 1998
"... Abstract: A comparison study of the efficiency and accuracy of a variety of meshless trial and test functions is presented in this paper, based on the general concept of the meshless local PetrovGalerkin (MLPG) method. 5 types of trial functions, and 6 types of test functions are explored. Differe ..."
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Cited by 312 (54 self)
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examples show that all of the MLPG methods possess excellent rates of convergence, for both the unknown variables and their derivatives. An analysis of computational costs shows that the MLPG5 method is less expensive, both in computational costs as well as definitely in humanlabor costs, than the FEM
The Relevance Vector Machine
, 2000
"... The support vector machine (SVM) is a stateoftheart technique for regression and classification, combining excellent generalisation properties with a sparse kernel representation. However, it does suffer from a number of disadvantages, notably the absence of probabilistic outputs, the requirement ..."
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Cited by 294 (6 self)
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The support vector machine (SVM) is a stateoftheart technique for regression and classification, combining excellent generalisation properties with a sparse kernel representation. However, it does suffer from a number of disadvantages, notably the absence of probabilistic outputs
Object recognition with features inspired by visual cortex
 CVPR’05 Volume
, 2005
"... We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position and scaletolerant edgedetectors over neighboring positions and multiple orientations. Our system’s architecture is motivated by a quantitative model of v ..."
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Cited by 291 (17 self)
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of visual cortex. We show that our approach exhibits excellent recognition performance and outperforms several stateoftheart systems on a variety of image datasets including many different object categories. We also demonstrate that our system is able to learn from very few examples. The performance
Learning multiple layers of features from tiny images
, 2009
"... Groups at MIT and NYU have collected a dataset of millions of tiny colour images from the web. It is, in principle, an excellent dataset for unsupervised training of deep generative models, but previous researchers who have tried this have found it difficult to learn a good set of filters from the ..."
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Cited by 280 (5 self)
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Groups at MIT and NYU have collected a dataset of millions of tiny colour images from the web. It is, in principle, an excellent dataset for unsupervised training of deep generative models, but previous researchers who have tried this have found it difficult to learn a good set of filters from
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