The Expectation Maximization Algorithm

By Frank Dellaert. 2002

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Citations in the corpus

Detection and Continual Learning of Novel Face Presentation Attacks (2021, background): “Estimating the GMM parameters is usually performed through expectation maximization (EM) [16], which can be a computationally expensive procedure.”
Iterative Channel Estimation Using LSE and Sparse Message Passing for MmWave MIMO Systems (2016, methodology): “2) EM update for the sparsity ratio: We now present a classical EM algorithm [31], [56] to learn the sparsity ratio η.”
Off-grid Channel Estimation with Sparse Bayesian Learning for OTFS Systems (2021, methodology): “An EM algorithm [23] is employed for updating the hyper-parameters in the (t+ 1)-th iteration:”
An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning (2020, methodology): “To estimate the model parameters of the JD-GMM, expectation-maximization (EM) algorithm [118]–[121] is used to maximize likelihood on the training data.”
Events Detection for an Audio-Based Surveillance System (2005, methodology): “The parameters of the models are estimated using the traditional Expectation-Maximization algorithm [7] initialized by a basic binary splitting vector quantization algorithm.”
The Impact of High School Size on Math Achievement and Dropout Rate (2009, methodology): “We imputed missing data using the Expectation Maximization (EM) algorithm (for a detailed explanation, see Dellaert, 2002).”
Source camera identification based on CFA interpolation (2005, background): “These two steps are iterated until convergence [8].”
A Global Human Settlement Layer From Optical HR/VHR RS Data: Concept and First Results (2013, methodology): “The parameters , , , of this model can be inferred by Expectation Maximization [68].”