Results 1 - 10 of 54,567

Designing Reusable Classes.

by Ralph E Johnson , Brian Foote - Journal of Object Oriented Programming , 1988
"... Abstract Object-oriented programming is as much a different way of designing programs as it is a different way of designing programming languages. This paper describes what it is like to design systems in Smalltalk. In particular, since a major motivation for object-oriented programming is software ..."
Abstract - Cited by 614 (9 self) - Add to MetaCart
Abstract Object-oriented programming is as much a different way of designing programs as it is a different way of designing programming languages. This paper describes what it is like to design systems in Smalltalk. In particular, since a major motivation for object-oriented programming

The PASCAL Visual Object Classes (VOC) Challenge

by M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, A. Zisserman - INTERNATIONAL JOURNAL OF COMPUTER VISION
"... ... and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection. ..."
Abstract - Cited by 629 (20 self) - Add to MetaCart
. This paper describes the dataset and evaluation procedure. We review the state-of-the-art in evaluated methods for both classification and detection, analyse whether the methods are statistically different, what they are learning from the images (e.g. the object or its context), and what the methods find

Justice and the politics of difference

by Diane H. Young, John W , 1990
"... Educators frequently recommend that children read aloud to parents at home in the belief that the activity will positively contribute to children's literacy growth. From a research perspective, however, little is known about these at-home reading experiences. Using a social constructivist theor ..."
Abstract - Cited by 511 (0 self) - Add to MetaCart
, middle-class community participated in the project. Accelerated and at-risk third grade readers took home a tape recorder and a third grade science text to read aloud to mothers. The conversations were audiotaped, professionally transcribed, and then coded. Results of the study indicated

Learning to predict by the methods of temporal differences

by Richard S. Sutton - MACHINE LEARNING , 1988
"... This article introduces a class of incremental learning procedures specialized for prediction – that is, for using past experience with an incompletely known system to predict its future behavior. Whereas conventional prediction-learning methods assign credit by means of the difference between predi ..."
Abstract - Cited by 1521 (56 self) - Add to MetaCart
This article introduces a class of incremental learning procedures specialized for prediction – that is, for using past experience with an incompletely known system to predict its future behavior. Whereas conventional prediction-learning methods assign credit by means of the difference between

A modular three-dimensional finite-difference ground-water flow model

by Model (michael Mcdonald, Arlen Harbaugh - U.S. Geological Survey Techniques of WaterResources Investigations Book 6, Chapter A1 , 1988
"... The primary objective of this course is to discuss the principals of finite difference methods and their applications in groundwater modeling. The emphasis of the class lectures is on the theoretical aspects of numerical modeling (finite difference method). Steps involved in simulation of groundwate ..."
Abstract - Cited by 508 (5 self) - Add to MetaCart
The primary objective of this course is to discuss the principals of finite difference methods and their applications in groundwater modeling. The emphasis of the class lectures is on the theoretical aspects of numerical modeling (finite difference method). Steps involved in simulation

Excitatory and inhibitory interactions in localized populations of model

by Hugh R. Wilson, Jack D. Cowan - Biophysics , 1972
"... ABSMAcr Coupled nonlinear differential equations are derived for the dynamics of spatially localized populations containing both excitatory and inhibitory model neurons. Phase plane methods and numerical solutions are then used to investigate population responses to various types of stimuli. The res ..."
Abstract - Cited by 495 (11 self) - Add to MetaCart
in response to one class of stimuli implies the existence of multiple stable states and hysteresis in response to a different class of stimuli. The relation between these findings and a number of experiments is discussed.

Maximum Likelihood Phylogenetic Estimation from DNA Sequences with Variable Rates over Sites: Approximate Methods

by Ziheng Yang - J. Mol. Evol , 1994
"... Two approximate methods are proposed for maximum likelihood phylogenetic estimation, which allow variable rates of substitution across nucleotide sites. Three data sets with quite different characteristics were analyzed to examine empirically the performance of these methods. The first, called ..."
Abstract - Cited by 557 (29 self) - Add to MetaCart
to their rates predicted assuming the star tree. Sites in different classes are then assumed to be evolving at these fixed rates when other tree topologies are evaluated.

The Askey-scheme of hypergeometric orthogonal polynomials and its q-analogue

by Roelof Koekoek, René F. Swarttouw , 1998
"... We list the so-called Askey-scheme of hypergeometric orthogonal polynomials and we give a q-analogue of this scheme containing basic hypergeometric orthogonal polynomials. In chapter 1 we give the definition, the orthogonality relation, the three term recurrence relation, the second order differenti ..."
Abstract - Cited by 578 (6 self) - Add to MetaCart
differential or difference equation, the forward and backward shift operator, the Rodrigues-type formula and generating functions of all classes of orthogonal polynomials in this scheme. In chapter 2 we give the limit relations between different classes of orthogonal polynomials listed in the Askey

Distance metric learning for large margin nearest neighbor classification

by Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul - In NIPS , 2006
"... We show how to learn a Mahanalobis distance metric for k-nearest neighbor (kNN) classification by semidefinite programming. The metric is trained with the goal that the k-nearest neighbors always belong to the same class while examples from different classes are separated by a large margin. On seven ..."
Abstract - Cited by 695 (14 self) - Add to MetaCart
We show how to learn a Mahanalobis distance metric for k-nearest neighbor (kNN) classification by semidefinite programming. The metric is trained with the goal that the k-nearest neighbors always belong to the same class while examples from different classes are separated by a large margin

Imagenet classification with deep convolutional neural networks.

by Alex Krizhevsky , Ilya Sutskever , Geoffrey E Hinton - In Advances in the Neural Information Processing System, , 2012
"... Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the pr ..."
Abstract - Cited by 1010 (11 self) - Add to MetaCart
Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than
Results 1 - 10 of 54,567