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991.
Boosted Bayesian network classifiers 总被引:2,自引:0,他引:2
The use of Bayesian networks for classification problems has received a significant amount of recent attention. Although computationally
efficient, the standard maximum likelihood learning method tends to be suboptimal due to the mismatch between its optimization
criteria (data likelihood) and the actual goal of classification (label prediction accuracy). Recent approaches to optimizing
classification performance during parameter or structure learning show promise, but lack the favorable computational properties
of maximum likelihood learning. In this paper we present boosted Bayesian network classifiers, a framework to combine discriminative
data-weighting with generative training of intermediate models. We show that boosted Bayesian network classifiers encompass
the basic generative models in isolation, but improve their classification performance when the model structure is suboptimal.
We also demonstrate that structure learning is beneficial in the construction of boosted Bayesian network classifiers. On
a large suite of benchmark data-sets, this approach outperforms generative graphical models such as naive Bayes and TAN in
classification accuracy. Boosted Bayesian network classifiers have comparable or better performance in comparison to other
discriminatively trained graphical models including ELR and BNC. Furthermore, boosted Bayesian networks require significantly
less training time than the ELR and BNC algorithms. 相似文献
992.
Inductive transfer with context-sensitive neural networks 总被引:1,自引:1,他引:0
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer which uses a single output neural network and additional contextual inputs
for learning multiple tasks. Motivated by problems with the application of MTL networks to machine lifelong learning systems,
csMTL encoding of multiple task examples was developed and found to improve predictive performance. As evidence, the csMTL method is tested on seven task domains and shown to produce hypotheses for primary tasks that are often better than standard
MTL hypotheses when learning in the presence of related and unrelated tasks. We argue that the reason for this performance
improvement is a reduction in the number of effective free parameters in the csMTL network brought about by the shared output node and weight update constraints due to the context inputs. An examination
of IDT and SVM models developed from csMTL encoded data provides initial evidence that this improvement is not shared across all machine learning models. 相似文献
993.
Haoqiang Jin Barbara Chapman Lei Huang Dieter an Mey Thomas Reichstein 《International journal of parallel programming》2008,36(3):312-325
We describe a performance study of a multi-zone application benchmark implemented in several OpenMP approaches that exploit
multi-level parallelism and deal with unbalanced workload. The multi-zone application was derived from the well-known NAS
Parallel Benchmarks (NPB) suite that involves flow solvers on collections of loosely coupled discretization meshes. Parallel
versions of this application have been developed using the Subteam concept and Workqueuing model as extensions to the current
OpenMP. We examine the performance impact of these extensions to OpenMP and compare with hybrid and nested OpenMP approaches
on several large parallel systems. 相似文献
994.
In this paper we extend the idea of interpolated coefficients for semilinear problems to the finite volume element method
based on rectangular partition. At first we introduce bilinear finite volume element method with interpolated coefficients
for a boundary value problem of semilinear elliptic equation. Next we derive convergence estimate in H
1-norm and superconvergence of derivative. Finally an example is given to illustrate the effectiveness of the proposed method.
This work is supported by Program for New Century Excellent Talents in University of China State Education Ministry, National
Science Foundation of China, the National Basic Research Program under the Grant (2005CB321703), the key project of China
State Education Ministry (204098), Scientific Research Fund of Hunan Provincial Education Department, China Postdoctoral Science
Foundation (No. 20060390894) and China Postdoctoral Science Foundation (No. 20060390894). 相似文献
995.
Todd Zickler Satya P. Mallick David J. Kriegman Peter N. Belhumeur 《International Journal of Computer Vision》2008,79(1):13-30
Complex reflectance phenomena such as specular reflections confound many vision problems since they produce image ‘features’
that do not correspond directly to intrinsic surface properties such as shape and spectral reflectance. A common approach
to mitigate these effects is to explore functions of an image that are invariant to these photometric events. In this paper
we describe a class of such invariants that result from exploiting color information in images of dichromatic surfaces. These
invariants are derived from illuminant-dependent ‘subspaces’ of RGB color space, and they enable the application of Lambertian-based
vision techniques to a broad class of specular, non-Lambertian scenes. Using implementations of recent algorithms taken from
the literature, we demonstrate the practical utility of these invariants for a wide variety of applications, including stereo,
shape from shading, photometric stereo, material-based segmentation, and motion estimation. 相似文献
996.
Analysis of Two-Dimensional Non-Rigid Shapes 总被引:1,自引:0,他引:1
Alexander M. Bronstein Michael M. Bronstein Alfred M. Bruckstein Ron Kimmel 《International Journal of Computer Vision》2008,78(1):67-88
Analysis of deformable two-dimensional shapes is an important problem, encountered in numerous pattern recognition, computer
vision and computer graphics applications. In this paper, we address three major problems in the analysis of non-rigid shapes:
similarity, partial similarity, and correspondence. We present an axiomatic construction of similarity criteria for deformation-invariant
shape comparison, based on intrinsic geometric properties of the shapes, and show that such criteria are related to the Gromov-Hausdorff
distance. Next, we extend the problem of similarity computation to shapes which have similar parts but are dissimilar when
considered as a whole, and present a construction of set-valued distances, based on the notion of Pareto optimality. Finally,
we show that the correspondence between non-rigid shapes can be obtained as a byproduct of the non-rigid similarity problem.
As a numerical framework, we use the generalized multidimensional scaling (GMDS) method, which is the numerical core of the
three problems addressed in this paper. 相似文献
997.
This paper addresses the question: at the level of cortical cells present in the primary area V1, is the information sufficient to extract the local perspective from the texture? Starting from a model of complex cells in visual area V1, we propose a biologically plausible algorithm for frequency analysis applied to the shape from texture problem. First, specific log-normal filters are designed in replacement of the classical Gabor filters because of their theoretical properties and of their biological plausibility. These filters are separable in frequency and orientation and they better sample the image spectrum which makes them appropriate for any pattern analysis technique. A method to estimate the local frequency in the image, which discards the need to choose the best local scale, is designed. Based on this frequency analysis model, a local decomposition of the image into patches leads to the estimation of the local frequency variation which is used to solve the problem of recovering the shape from the texture. From the analytical relation between the local frequency and the geometrical parameters, under perspective projection, it is possible to recover the orientation and the shape of the original image. The accuracy of the method is evaluated and discussed on different kind of textures, both regular and irregular, with planar and curved surfaces and also on natural scenes and psychophysical stimuli. It compares favorably to the best existing methods, with in addition, a low computational cost. The biological plausibility of the model is finally discussed. 相似文献
998.
Tal Nir Alfred M. Bruckstein Ron Kimmel 《International Journal of Computer Vision》2008,76(2):205-216
A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis
functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized
representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood
based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few
parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components
at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing
for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very
general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant
basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to
the best results published so far. 相似文献
999.
On conditional diagnosability and reliability of the BC networks 总被引:1,自引:1,他引:0
Qiang Zhu 《The Journal of supercomputing》2008,45(2):173-184
An n-dimensional bijective connection network (in brief, BC network), denoted by X n , is an n-regular graph with 2 n nodes and n2 n?1 edges. Hypercubes, crossed cubes, twisted cubes, and Möbius cubes all belong to the class of BC networks (Fan and He in Chin. J. Comput. 26(1):84–90, [2003]). We prove that the super connectivity of X n is 2n?2 for n≥3 and the conditional diagnosability of X n is 4n?7 for n≥5. As a corollary of this result, we obtain the super connectivity and conditional diagnosability of the hypercubes, twisted cubes, crossed cubes, and Möbius cubes. 相似文献
1000.
Grid computing, which is characterized by large-scale sharing and collaboration of dynamic distributed resources has quickly
become a mainstream technology in distributed computing and is changing the traditional way of software development. In this
article, we present a grid-based software testing framework for unit and integration test, which takes advantage of the large-scale
and cost-efficient computational grid resources to establish a testbed for supporting automated software test in complex software
applications. Within this software testing framework, a dynamic bag-of-tasks model using swarm intelligence is developed to
adaptively schedule unit test cases. Various high-confidence computing mechanisms, such as redundancy, intermediate value
checks, verification code injection, and consistency checks are employed to verify the correctness of each test case execution
on the grid. Grid workflow is used to coordinate various test units for integration test. Overall, we expect that the grid-based
software testing framework can provide efficient and trustworthy services to significantly accelerate the testing process
with large-scale software testing.
相似文献
Yong-Duan SongEmail: |