Search - variational bayes

Search - variational bayes - List

[Software Engineering] Hierarchical-Dirichlet-Processes DL : 0: 详细论述了分层狄利克雷模型，以及此模型在机器学习中的应用-Layered detail Dirichlet model, as well as this model in the application of machine learning
Update : 2025-02-17 Size : 218kb Publisher : chunxiao
[matlab] VBEMGMM DL : 0: Variational Bayes by EmtiyazKhan
Update : 2025-02-17 Size : 23kb Publisher : angshul
[Program doc] A-Bayesian-Approach DL : 0: In this paper, we propose a Bayesian methodology for receiver function analysis, a key tool in determining the deep structure of the Earth’s crust.We exploit the assumption of sparsity for receiver functions to develop a Bayesian deconvolution method as an alternative to the widely used iterative deconvolution.We model samples of a sparse signal as i.i.d. Student-t random variables. Gibbs sampling and variational Bayes techniques are investigated for our specific posterior inference problem. We used those techniques within the expectation-maximization (EM) algorithm to estimate our unknown model parameters. The superiority of the Bayesian deconvolution is demonstrated by the experiments on both simulated and real earthquake data.
Update : 2025-02-17 Size : 3.2mb Publisher : 张洋
[Graph Recognize] Pattern_Recognition_and_Machine_Learning__Informa DL : 0: Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.
Update : 2025-02-17 Size : 4.34mb Publisher : sas
[Special Effects] onlineHDP_CPP.tar DL : 0: OnlineHDP代码，实现HDP算法ONLINE VARIATIONAL BAYES FOR HIERARCHICAL DIRICHLET PROCE-OnlineHDP code, HDP algorithm ONLINE VARIATIONAL BAYES FOR HIERARCHICAL DIRICHLET PROCESS
Update : 2025-02-17 Size : 889kb Publisher : dakaren
[Other] Machine-Learnin DL : 0: 机器学习(Machine Learning, ML)是一门多领域交叉学科，涉及概率论、统计学、逼近论、凸分析、算法复杂度理论等多门学科。专门研究计算机怎样模拟或实现人类的学习行为，以获取新的知识或技能，重新组织已有的知识结构使之不断改善自身的性能-Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.
Update : 2025-02-17 Size : 7.59mb Publisher : 王以良
[matlab] lda-0.2-matlab.tar DL : 0: lda的matlab实现，lda is a Latent Dirichlet Allocation (Blei et al., 2001) package written both in MATLAB and C (command line interface). This package provides only a standard variational Bayes estimation that was first proposed, but has a simple textual data format that is almost the same as SVMlight or TinySVM. This package can be used as an aid to understand LDA, or simply as a regularized alternative to PLSI, which has a severe overfitting problem due to its maximum likelihood structure. For advanced users who wish to benefit from the latest result, consider using npbayes or MPCA: though, they have data formats different from above.-lda is a Latent Dirichlet Allocation (Blei et al., 2001) package written both in MATLAB and C (command line interface). This package provides only a standard variational Bayes estimation that was first proposed, but has a simple textual data format that is almost the same as SVMlight or TinySVM. This package can be used as an aid to understand LDA, or simply as a regularized alternative to PLSI, which has a severe overfitting problem due to its maximum likelihood structure. For advanced users who wish to benefit from the latest result, consider using npbayes or MPCA: though, they have data formats different from above.
Update : 2025-02-17 Size : 24kb Publisher : 乌龟
[Software Engineering] A-Robust-Algorithm-for-Joint-Sparse DL : 0: 脉冲噪声背景下的联合稀疏恢复方法，在不同背景下给出了测试结果-presents a robust solution for joint sparse recovery (JSR) under impulsive noise. The unknown measurement noise is endowed with the Student-t distribution, then a novel Bayesian probabilistic model is proposed to describe the JSR problem. To effectively recover the joint row sparse signal, variational Bayes (VB) method is introduced for Bayesian theory based JSR algorithms such that it overcomes the intractable integrations inherent. Simulation results verify that the proposed algorithm significantly outperforms the existing algorithms under impulsive noise.
Update : 2025-02-17 Size : 1.12mb Publisher : bigbigtom