作者: 大喘氣 時(shí)間: 2025-3-21 21:57
Several Enhancements to Hermite-Based Approximation of One-Variable Functionscted from the function contributes to the error decrease. We demonstrate how to choose that bias. Secondly we show how to select a basis among orthonormal functions to achieve minimum error for a fixed dimension of an approximation space. Thirdly we prove that loss of orthonormality due to truncatio作者: Etymology 時(shí)間: 2025-3-22 01:40 作者: olfction 時(shí)間: 2025-3-22 05:30 作者: Pandemic 時(shí)間: 2025-3-22 09:51
Generalization of Concave and Convex Decomposition in Kikuchi Free Energyon processing. The minimum of Kikuchi free energy is known to yield more accurate marginals than that of Bethe free energy. Concave convex procedure (CCCP) proposed by Yuille is known to be an algorithm which guarantees to monotonically decrease both free energies..In this paper, we generalize CCCP 作者: Microaneurysm 時(shí)間: 2025-3-22 15:03 作者: 琺瑯 時(shí)間: 2025-3-22 20:05
Global Dynamics of Finite Cellular Automatae local rules of elementary cellular automata are deduced and the cellular automata configurations are represented via Fourier analysis. This allows for a further analysis of the global dynamics of cellular automata by the use of tools derived from functional analysis and dynamical system theory.作者: VEST 時(shí)間: 2025-3-23 00:07 作者: Arroyo 時(shí)間: 2025-3-23 03:28 作者: 最高點(diǎn) 時(shí)間: 2025-3-23 08:10
BICA: A Boolean Indepenedent Component Analysis Approachtors at an intermediate step of a clustering procedure aimed at taking decisions from data. With a “divide et conquer” strategy we first look for a suitable representation of the data and then assign them to clusters. We assume a Boolean coding to be a proper representation of the input of the discr作者: pus840 時(shí)間: 2025-3-23 13:39
Improving the Learning Speed in 2-Layered LSTM Network by Estimating the Configuration of Hidden Unifor function approximation tasks. The motivation of this method is based on the behavior of the hidden units and the complexity of the function to be approximated. The results obtained for 1-D and 2-D functions show that the proposed methodology improves the network performance, stabilizing the trai作者: 全面 時(shí)間: 2025-3-23 17:31 作者: 公共汽車 時(shí)間: 2025-3-23 21:00 作者: 消毒 時(shí)間: 2025-3-23 22:53
OP-ELM: Theory, Experiments and a Toolboxgression and classification problems. The results are compared with widely known Multilayer Perceptron (MLP) and Least-Squares Support Vector Machine (LS-SVM) methods. As the experiments (regression and classification) demonstrate, the OP-ELM methodology is considerably faster than the MLP and the L作者: stroke 時(shí)間: 2025-3-24 06:05 作者: Culpable 時(shí)間: 2025-3-24 06:39 作者: 受人支配 時(shí)間: 2025-3-24 12:47
Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimatired models in the context of reproducing kernel Hilbert spaces. In this setting the task of input selection is converted into the task of selecting functional components depending on one (or more) inputs. In turn the process of learning with embedded selection of such components can be formalized as作者: Prologue 時(shí)間: 2025-3-24 15:57 作者: Tartar 時(shí)間: 2025-3-24 19:15
Aus der Vorgeschichte des Zeppelins,We present a training method which adjusts the weights of the MLP (Multilayer Perceptron) to preserve the distance invariance in a low dimensional space. We apply visualization techniques to display the detailed representations of the trained neurons.作者: 肥料 時(shí)間: 2025-3-25 00:08 作者: 先驅(qū) 時(shí)間: 2025-3-25 05:36 作者: 埋葬 時(shí)間: 2025-3-25 07:53 作者: CESS 時(shí)間: 2025-3-25 13:32
978-3-540-87535-2Springer-Verlag Berlin Heidelberg 2008作者: Daily-Value 時(shí)間: 2025-3-25 17:12 作者: 放氣 時(shí)間: 2025-3-25 23:52
Improving the Learning Speed in 2-Layered LSTM Network by Estimating the Configuration of Hidden Unifor function approximation tasks. The motivation of this method is based on the behavior of the hidden units and the complexity of the function to be approximated. The results obtained for 1-D and 2-D functions show that the proposed methodology improves the network performance, stabilizing the training phase.作者: oncologist 時(shí)間: 2025-3-26 03:39
Natural Conjugate Gradient on Complex Flag Manifolds for Complex Independent Subspace AnalysisRiemannian geometry, propose the natural conjugate gradient method on this class of manifolds. Numerical experiments demonstrate that the natural conjugate gradient method yields better convergence compared to the natural gradient geodesic search method.作者: 考博 時(shí)間: 2025-3-26 07:57 作者: muster 時(shí)間: 2025-3-26 08:44 作者: impale 時(shí)間: 2025-3-26 15:23 作者: affluent 時(shí)間: 2025-3-26 19:53 作者: 蓋他為秘密 時(shí)間: 2025-3-27 00:33
Anton Pech,Georg Pommer,Johannes Zeininger proposed for that purpose, but it cannot be directly applied to mixture models that do not belong to an exponential family. This paper proposes a method to apply the exponential family PCA to mixture models. A key idea is to embed mixtures into a space of an exponential family. The problem is that 作者: 點(diǎn)燃 時(shí)間: 2025-3-27 02:51
Verglasungs- und Beschlagstechnik,cted from the function contributes to the error decrease. We demonstrate how to choose that bias. Secondly we show how to select a basis among orthonormal functions to achieve minimum error for a fixed dimension of an approximation space. Thirdly we prove that loss of orthonormality due to truncatio作者: N防腐劑 時(shí)間: 2025-3-27 08:42
Anton Pech,Georg Pommer,Johannes Zeiningeridden-layer neural networks with fewer inner parameters can learn from such signals better than ordinary ones. We show that such neural networks can be used for approximating multi-category Bayesian discriminant functions when the state-conditional probability distributions are two dimensional norma作者: evince 時(shí)間: 2025-3-27 10:39 作者: POLYP 時(shí)間: 2025-3-27 14:17 作者: 不斷的變動 時(shí)間: 2025-3-27 20:37
N. C. Mamatha,Karthik Reddy Panyam Then, it is an important issue to clarify what is a source of the complex phenomena and to analyze what kind of response will emerge. Then, in this paper, we analyze deterministic chaos from a new aspect. The analysis method is based on the idea that attractors of nonlinear dynamical systems and ne作者: Brochure 時(shí)間: 2025-3-28 01:20 作者: 變量 時(shí)間: 2025-3-28 05:07 作者: 破布 時(shí)間: 2025-3-28 09:27
Diversity of , Microsymbionts in Moroccoilarity measurement between patterns has been introduced to make sure that spatial information in feature space, including both magnitude and phase of input vector, has been taken into consideration. By these improvements, the new ART2 architecture is characterized by the advantages: (i) keeping the作者: mettlesome 時(shí)間: 2025-3-28 11:38 作者: 缺陷 時(shí)間: 2025-3-28 16:51
Aus der Vorgeschichte des Zeppelins,for function approximation tasks. The motivation of this method is based on the behavior of the hidden units and the complexity of the function to be approximated. The results obtained for 1-D and 2-D functions show that the proposed methodology improves the network performance, stabilizing the trai作者: 性滿足 時(shí)間: 2025-3-28 20:47
https://doi.org/10.1007/978-3-322-82267-3al classifiers. Application of proposed approach visibly improves the results compared to the case of training without postulated enhancements..Moreover, a new measure of distance between events in the pattern space is proposed and tested with . model. Numerical results are very promising and outper作者: photophobia 時(shí)間: 2025-3-29 01:10 作者: patriot 時(shí)間: 2025-3-29 06:26 作者: canvass 時(shí)間: 2025-3-29 09:22 作者: Factorable 時(shí)間: 2025-3-29 11:25 作者: 瑣碎 時(shí)間: 2025-3-29 17:00
Sauerbruch und die NS-Forschung,red models in the context of reproducing kernel Hilbert spaces. In this setting the task of input selection is converted into the task of selecting functional components depending on one (or more) inputs. In turn the process of learning with embedded selection of such components can be formalized as作者: 我不怕犧牲 時(shí)間: 2025-3-29 22:00
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162630.jpg作者: PAEAN 時(shí)間: 2025-3-30 00:24 作者: 愛管閑事 時(shí)間: 2025-3-30 04:58
https://doi.org/10.1007/978-3-322-82267-3 without any prior models. Besides, we construct an efficient fixed-point algorithm for optimizing it by an approximate Newton’s method. Numerical experiments verify the effectiveness of the proposed method.作者: Implicit 時(shí)間: 2025-3-30 08:50
A New Type of ART2 Architecture and Application to Color Image Segmentationffective unsupervised segmentation of color image and it has been experimentally found to perform well in a modified ...... color space in which the perceptual color difference can be measured properly by spatial information.作者: 哺乳動物 時(shí)間: 2025-3-30 13:24 作者: 裙帶關(guān)系 時(shí)間: 2025-3-30 20:08 作者: 誹謗 時(shí)間: 2025-3-31 00:10
Anton Pech,Georg Pommer,Johannes Zeiningerthe embedding is not unique, and the dimensionality of parameter space is not constant when the numbers of mixture components are different. The proposed method finds a sub-optimal solution by linear programming formulation.作者: acetylcholine 時(shí)間: 2025-3-31 00:56 作者: ferment 時(shí)間: 2025-3-31 07:19
https://doi.org/10.1007/3-211-27572-X effects of high dimensionality for cross-validation of both hard- and soft-margin SVMs. Based on the theoretical proofs towards infinity we derive heuristics that can be easily used to validate whether or not given data sets are subject to these constraints.作者: 全國性 時(shí)間: 2025-3-31 10:53 作者: 暗語 時(shí)間: 2025-3-31 13:21 作者: Arthritis 時(shí)間: 2025-3-31 20:03 作者: 違抗 時(shí)間: 2025-4-1 00:10 作者: 博愛家 時(shí)間: 2025-4-1 05:27
Several Enhancements to Hermite-Based Approximation of One-Variable Functionsn of the argument range of the basis functions does not effect the overall error of approximation and the expansion coefficients. We show how this feature can be used. An application of the obtained results to ECG data compression is presented.作者: LAPSE 時(shí)間: 2025-4-1 07:17
Reliability of Cross-Validation for SVMs in High-Dimensional, Low Sample Size Scenarios effects of high dimensionality for cross-validation of both hard- and soft-margin SVMs. Based on the theoretical proofs towards infinity we derive heuristics that can be easily used to validate whether or not given data sets are subject to these constraints.作者: 打火石 時(shí)間: 2025-4-1 14:11 作者: Flatter 時(shí)間: 2025-4-1 14:58
