Optimal Transport for Gaussian Mixture Models [PDF]
IEEE Access, 2019 We introduce an optimal mass transport framework on the space of Gaussian mixture models. These models are widely used in statistical inference. Specifically, we treat the Gaussian mixture models as a submanifold of probability densities equipped with ...
Yongxin Chen +2 more
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Avoiding inferior clusterings with misspecified Gaussian mixture models [PDF]
Scientific Reports, 2023 Clustering is a fundamental tool for exploratory data analysis, and is ubiquitous across scientific disciplines. Gaussian Mixture Model (GMM) is a popular probabilistic and interpretable model for clustering.
Siva Rajesh Kasa, Vaibhav Rajan
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Fitting Gaussian mixture models on incomplete data [PDF]
BMC Bioinformatics, 2022 Background Bioinformatics investigators often gain insights by combining information across multiple and disparate data sets. Merging data from multiple sources frequently results in data sets that are incomplete or contain missing values.
Zachary R. McCaw +2 more
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Sharp Guarantees and Optimal Performance for Inference in Binary and Gaussian-Mixture Models [PDF]
Entropy, 2021 We study convex empirical risk minimization for high-dimensional inference in binary linear classification under both discriminative binary linear models, as well as generative Gaussian-mixture models.
Hossein Taheri +2 more
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A new iterative initialization of EM algorithm for Gaussian mixture models. [PDF]
PLoS ONE, 2023 BackgroundThe expectation maximization (EM) algorithm is a common tool for estimating the parameters of Gaussian mixture models (GMM). However, it is highly sensitive to initial value and easily gets trapped in a local optimum.MethodTo address these ...
Jie You, Zhaoxuan Li, Junli Du
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Gaussian Mixture Models for Control of Quasi-Passive Spinal Exoskeletons [PDF]
Sensors, 2020 Research and development of active and passive exoskeletons for preventing work related injuries has steadily increased in the last decade. Recently, new types of quasi-passive designs have been emerging.
Marko Jamšek, Tadej Petrič, Jan Babič
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Entropy-Based Volatility Analysis of Financial Log-Returns Using Gaussian Mixture Models [PDF]
EntropyVolatility in financial markets refers to the variation in asset prices over time. High volatility indicates increased risk, making its evaluation essential for effective risk management.
Luca Scrucca
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A study on Pufferfish privacy algorithm based on Gaussian mixture models [PDF]
Scientific ReportsIn real-world scenarios, mixture models are frequently employed to fit complex data, demonstrating remarkable flexibility and efficacy. This paper introduces an innovative Pufferfish privacy algorithm based on Gaussian priors, specifically designed for ...
Weisan Wu
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Correction: Fitting Gaussian mixture models on incomplete data [PDF]
BMC Bioinformatics, 2022 Zachary R. McCaw +2 more
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Computationally efficient multi-sample flow cytometry data analysis using Gaussian mixture models [PDF]
BMC BioinformaticsBackground An important challenge in flow cytometry (FCM) data analysis is making comparisons of corresponding cell populations across multiple FCM samples.
Philip Rutten +4 more
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