Results 1 - 10 of 1,798

Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late Nineteenth Century

by N. A. Rayner, D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, A. Kaplan - J. GEOPHYSICAL RESEARCH , 2003
"... ... data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1 ° latitude-longitude g ..."
Abstract - Cited by 539 (4 self) - Add to MetaCart
-longitude grid from 1871. The companion HadMAT1 runs monthly from 1856 on a 5 ° latitude-longitude grid and incorporates new corrections for the effect on NMAT of increasing deck (and hence measurement) heights. HadISST1 and HadMAT1 temperatures are reconstructed using a two-stage reducedspace optimal

Policy gradient methods for reinforcement learning with function approximation.

by Richard S Sutton , David Mcallester , Satinder Singh , Yishay Mansour - In NIPS, , 1999
"... Abstract Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and determining a policy from it has so far proven theoretically intractable. In this paper we explore an alternative approach in which the policy is explicitly repres ..."
Abstract - Cited by 439 (20 self) - Add to MetaCart
that the gradient can be written in a form suitable for estimation from experience aided by an approximate action-value or advantage function. Using this result, we prove for the first time that a version of policy iteration with arbitrary differentiable function approximation is convergent to a locally optimal

Svm-knn: Discriminative nearest neighbor classification for visual category recognition

by Hao Zhang, Alexander C. Berg, Michael Maire, Jitendra Malik - 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 ..."
Abstract - Cited by 342 (10 self) - Add to MetaCart
nearest neighbor classifiers are natural in this setting, they suffer from the problem of high variance (in bias-variance decomposition) in the case of limited sampling. Alternatively, one could use support vector machines but they involve time-consuming optimization and computation of pairwise distances

Large-scale simultaneous hypothesis testing: the choice of a null hypothesis

by Bradley Efron - JASA , 2004
"... Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously. This poses new difficulties for the statistician, but also opens new opportunities. In particular it allows empirical estimatio ..."
Abstract - Cited by 301 (15 self) - Add to MetaCart
discovery rate to examine the inference issues. Two genomics problems are used as examples to show the importance of correctly choosing the null hypothesis. Key Words: local false discovery rate, empirical Bayes, microarray analysis, empirical null hypothesis, unobserved covariates

Correct Architecture Refinement

by Mark Moriconi, Xiaolei Qian, R. A. Riemenschneider - IEEE Transactions on Software Engineering , 1995
"... A method is presented for the stepwise refinement of an abstract architecture into a relatively correct lower-level architecture that is intended to implement it. A refinement step involves the application of a predefined refinement pattern that provides a routine solution to a standard architectura ..."
Abstract - Cited by 206 (8 self) - Add to MetaCart
A method is presented for the stepwise refinement of an abstract architecture into a relatively correct lower-level architecture that is intended to implement it. A refinement step involves the application of a predefined refinement pattern that provides a routine solution to a standard

Multi-way distributional clustering via pairwise interactions

by Ron Bekkerman, Andrew Mccallum - In ICML , 2005
"... We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between the types, as observed in co-occurrence data. In this scheme, multiple clustering systems are generated aiming at maximi ..."
Abstract - Cited by 60 (10 self) - Add to MetaCart
at maximizing an objective function that measures multiple pairwise mutual information between cluster variables. To implement this idea, we propose an algorithm that interleaves top-down clustering of some variables and bottom-up clustering of the other variables, with a local optimization correction routine

Variational Inference for Bayesian Mixtures of Factor Analysers

by Zoubin Ghahramani, Matthew J. Beal - In Advances in Neural Information Processing Systems 12 , 2000
"... We present an algorithm that infers the model structure of a mixture of factor analysers using an ecient and deterministic variational approximation to full Bayesian integration over model parameters. This procedure can automatically determine the optimal number of components and the local dimension ..."
Abstract - Cited by 191 (22 self) - Add to MetaCart
We present an algorithm that infers the model structure of a mixture of factor analysers using an ecient and deterministic variational approximation to full Bayesian integration over model parameters. This procedure can automatically determine the optimal number of components and the local

Bayesian color constancy

by David H. Brainard, William T. Freeman - Journal of the Optical Society of America A , 1997
"... The problem of color constancy may be solved if we can recover the physical properties of illuminants and surfaces from photosensor responses. We consider this problem within the framework of Bayesian decision theory. First, we model the relation among illuminants, surfaces, and photosensor response ..."
Abstract - Cited by 188 (23 self) - Add to MetaCart
mass (MLM) estimate, that integrates local probability density. The new method uses an optimality criterion that is appropriate for perception tasks: It finds the most probable approximately correct answer. For the case of low observation noise, we provide an efficient approximation. We develop the MLM

Adaptive Least Squares Correlation: A Powerful Image Matching Technique

by A W Gruen - South African Journal of Photogrammetry, Remote Sensing and Cartography , 1985
"... The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its application to image matching is outlined. It allows for simultaneous radiometric corrections and local geometrical image shaping, whereby the system parameters are automa ..."
Abstract - Cited by 182 (31 self) - Add to MetaCart
The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its application to image matching is outlined. It allows for simultaneous radiometric corrections and local geometrical image shaping, whereby the system parameters

Coil sensitivity encoding for fast MRI. In:

by Klaas P Pruessmann , Markus Weiger , Markus B Scheidegger , Peter Boesiger - Proceedings of the ISMRM 6th Annual Meeting, , 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
Abstract - Cited by 193 (3 self) - Add to MetaCart
or collimation but by spectral analysis. The idea of Lauterbur (1) to encode object contrast in the resonance spectrum by a magnetic field gradient forms the exclusive basis of signal localization in Fourier imaging. However powerful, the gradient-encoding concept implies a fundamental restriction. Only one
Results 1 - 10 of 1,798