Results 41 to 50 of about 1,500,611 (328)

A moment-distance hybrid method for estimating a mixture of two symmetric densities

Modern Stochastics: Theory and Applications, 2018
In clustering of high-dimensional data a variable selection is commonly applied to obtain an accurate grouping of the samples. For two-class problems this selection may be carried out by fitting a mixture distribution to each variable.
David Källberg, Yuri Belyaev, Patrik Rydén   +2 more
doaj   +1 more source

Random group recommendation model based on fuzzy clustering

Journal of Electronic Science and Technology, 2020
The group recommendation system is a viral requirement for the Internet service provider to provide recommendation services for all the users in a group.
Zhe Ding, Zhen Qin, Qi-Xu Wang, Zhi-Guang Qin   +3 more
doaj   +1 more source

PMSSC: Parallelizable multi-subset based self-expressive model for subspace clustering

Computational Visual Media, 2023
Subspace clustering methods which embrace a self-expressive model that represents each data point as a linear combination of other data points in the dataset provide powerful unsupervised learning techniques.
Katsuya Hotta, Takuya Akashi, Shogo Tokai, Chao Zhang   +3 more
doaj   +1 more source

RNN Language Model with Word Clustering and Class-based Output Layer [PDF]

, 2013
The recurrent neural network language model (RNNLM) has shown significant promise for statistical language modeling. In this work, a new class-based output layer method is introduced to further improve the RNNLM. In this method, word class information is
Johnson, Michael T, Liu, Jia, Shi, Yongzhe, Zhang, Wei-Qiang   +3 more
core   +2 more sources

Model‐based clustering of longitudinal data [PDF]

Canadian Journal of Statistics, 2010
AbstractA new family of mixture models for the model‐based clustering of longitudinal data is introduced. The covariance structures of eight members of this new family of models are given and the associated maximum likelihood estimates for the parameters are derived via expectation–maximization (EM) algorithms.
McNicholas, Paul D., Murphy, Thomas Brendan   +1 more
openaire   +3 more sources

Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM

FEBS Letters, EarlyView.
Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley   +1 more source

Human-Interpretable Time-Series Feature Extraction Using Model-Based Clustering

IEEE Access
Feature extraction is an essential task for Deep Neural Networks (DNNs), as high-dimensional data are often available and filtering can highlight relevant patterns for the reconstruction or forecasting of a target.
Joao Eduardo Hoffmann, Asad Waqar Malik, Max Mauro Dias Santos, Joao Francisco Justo   +3 more
doaj   +1 more source

Mapping the evolution of mitochondrial complex I through structural variation

FEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin, Tingting Chen, James A. Letts   +2 more
wiley   +1 more source

Organoids in pediatric cancer research

FEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

Model-based clustering via linear cluster-weighted models

, 2015
A novel family of twelve mixture models with random covariates, nested in the linear $t$ cluster-weighted model (CWM), is introduced for model-based clustering.
Aitken, Andrews, Andrews, Antonio Punzo, Baek, Biernacki, Brent, Böhning, Campbell, Cellini, Chatzis, Cleveland, Dempster, Everitt, Flury, Fraley, Frühwirth-Schnatter, Gershenfeld, Greselin, Hennig, Hubert, Ingrassia, Lange, Leisch, McLachlan, McLachlan, McNicholas, McNicholas, McNicholas, McNicholas, Peel, Salvatore Ingrassia, Schwarz, Shoham, Simona C. Minotti, Titterington, Wand, Wedel, Zellner   +38 more
core   +1 more source