FIGURE 15.1.MLE for Gaussian model. AGaussian mixture model, defined by q(x;θ)=∑ℓ=1mwℓN(x;μℓ,Σℓ), is suitable to approximate such multimodal distributions. Here,N(x;μ,Σ)denotes a Gaussian model with expectationμand variance-covariance matrixΣ: ...
2. 用Gibbs Sampling来做Approximate Inference Gibbs Sampling是一个经典的graphical models inference technique。当然在我们这个context里面,我们并没有在任何的parameter上设定prior。所以我们只能在上面加上noninformative prior,借此来迫近没有加prior的情况。 具体来说呢我们在categorical parameter上加上uniform的prior,然...
Intuitively, this model can be imagined as Gaussian model being bent at the first principal axis. For estimating parameters of mixtures of this model, the EM algorithm is employed. Experiments on synthetic data and Chinese characters show that the proposed nonlinear mixture models can approximate ...
Abstract We propose a greedy variational method for decomposing a non-negative multivariate signal as a weighted sum of Gaussians, which, borrowing the terminology from statistics, we refer to as a Gaussian mixture model. Notably, our method has the following features: (1) It accepts multivariate...
Yu, L., Yang, T., Chan, A.B.: Density-preserving hierarchical EM algorithm: simplifying Gaussian mixture models for approximate inference. IEEE Trans. Pattern Anal. Mach. Intell. 41(6), 1323–1337 (2019) Article Google Scholar Ding, J., Tarokh, V., Yang, Y.: Model selection techniq...
High-Dimensional Non-Gaussian Data Clustering using Variational Learning of Mixture Models The main idea of variational inference is to approximate the model posterior distribution by minimizing the Kullback-Leibler divergence between the exact (or true) posterior and an approximating distribution. Recently...
tion. That is, our goal is to approximate p (x i |y) = 1 Z t i (x i ) dx \i p 0 (x) j =i t j (x j ) , (1) where we used shorthand notation t i (x i )≡ p(y i |x i ) and with normalization constant Z = dx p 0 (x) i t i (x i ) , (2) which...
The generalized Gaussian (GG) distributions introduces one additional shape parameter compared to the Gaussian model, and it can approximate a large class of statistical distributions [22]. Indeed, the shape parameter tunes the decay rate of the density function, and thus describes the shape ...
(Lin et al., 2021), and the system-level voltage limit risk index and power flow limit risk index are established. However, the Cornish-Fisher series semi-invariant method is an approximate method and its computational complexity is high, which may lead to insufficient accuracy when dealing ...
本文提出了一种在相控阵雷达回波数据序列中用高斯混合体模型 (GMM)检测与跟踪运动目标的在线算法 。 First,a GMM (Gaussian mixture model) is used to approximate values of a particular pixel of the ra...