Results 91 to 100 of about 8,286,998 (397)
FEBS Letters, EarlyView.Interaction extracellular vesicles (iEVs) are hybrid vesicles formed through host‐pathogen communication. They facilitate immune evasion, transfer pathogens' molecules, increase host cell uptake, and enhance virulence. This Perspective article illustrates the multifunctional roles of iEVs and highlights their emerging relevance in infection dynamics ...
Bruna Sabatke +2 more
wiley +1 more source
Non-negative Dimensionality Reduction for Mammogram Classification [PDF]
Journal of Electrical and Electronics Engineering, 2009 Directly classifying high dimensional datamay exhibit the ``curse of dimensionality'' issue thatwould negatively influence the classificationperformance with an increase in the computationalload, depending also on the classifier structure.
I. Buciu, A. Gacsadi
doaj
Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions [PDF]
Found. Trends Mach. Learn., 2016 Modern applications in engineering and data science are increasinglybased on multidimensional data of exceedingly high volume, variety,and structural richness.
A. Cichocki +5 more
semanticscholar +1 more source
Spectral dimensionality reduction for HMMs [PDF]
, 2012 Hidden Markov Models (HMMs) can be accurately approximated using co-occurrence frequencies of pairs and triples of observations by using a fast spectral method in contrast to the usual slow methods like EM or Gibbs sampling.
Foster, Dean P. +2 more
core +2 more sources
Sequential Dimensionality Reduction for Extracting Localized Features
, 2016 Linear dimensionality reduction techniques are powerful tools for image analysis as they allow the identification of important features in a data set. In particular, nonnegative matrix factorization (NMF) has become very popular as it is able to extract ...
Casalino, Gabriella, Gillis, Nicolas
core +1 more source
Autophagy in cancer and protein conformational disorders
FEBS Letters, EarlyView.Autophagy plays a crucial role in numerous biological processes, including protein and organelle quality control, development, immunity, and metabolism. Hence, dysregulation or mutations in autophagy‐related genes have been implicated in a wide range of human diseases.
Sergio Attanasio
wiley +1 more source
DROP: Dimensionality Reduction Optimization for Time Series
, 2019 Dimensionality reduction is a critical step in scaling machine learning pipelines. Principal component analysis (PCA) is a standard tool for dimensionality reduction, but performing PCA over a full dataset can be prohibitively expensive.
Bailis, Peter, Suri, Sahaana
core +1 more source
Adaptive Metric Dimensionality Reduction [PDF]
Theoretical Computer Science, 2013 We study adaptive data-dependent dimensionality reduction in the context of supervised learning in general metric spaces. Our main statistical contribution is a generalization bound for Lipschitz functions in metric spaces that are doubling, or nearly doubling.
Aryeh Kontorovich +2 more
openaire +4 more sources
A stepwise emergence of evolution in the RNA world
FEBS Letters, EarlyView.How did biological evolution emerge from chemical reactions? This perspective proposes a gradual scenario of self‐organization among RNA molecules, where catalytic feedback on random mixtures plays the central role. Short oligomers cross‐ligate, and self‐assembly enables heritable variations. An event of template‐externalization marks the transition to
Philippe Nghe
wiley +1 more source
Reduction algorithm based on supervised discriminant projection for network security data
Tongxin xuebao, 2021 In response to the problem that for dimensionality reduction, traditional manifold learning algorithm did not consider the raw data category information, and the degree of clustering was generally at a low level, a manifold learning dimensionality ...
Fangfang GUO +3 more
doaj +2 more sources