Results 131 to 140 of about 8,286,998 (397)

EncoderMap: Dimensionality Reduction and Generation of Molecule Conformations.

Journal of Chemical Theory and Computation, 2019
Molecular simulation is one example where large amounts of high-dimensional (high-d) data are generated. To extract useful information, e.g., about relevant states and important conformational transitions, a form of dimensionality reduction is required ...
Tobias Lemke, C. Peter
semanticscholar   +1 more source

Randomized Dimensionality Reduction for k-means Clustering [PDF]

, 2013
We study the topic of dimensionality reduction for $k$-means clustering. Dimensionality reduction encompasses the union of two approaches: \emph{feature selection} and \emph{feature extraction}.
Boutsidis, Christos, Drineas, Petros, Mahoney, Michael W., Zouzias, Anastasios   +3 more
core  

Stochastic variation in the FOXM1 transcription program mediates replication stress tolerance

Molecular Oncology, EarlyView.
Cellular heterogeneity is a major cause of drug resistance in cancer. Segeren et al. used single‐cell transcriptomics to investigate gene expression events that correlate with sensitivity to the DNA‐damaging drugs gemcitabine and prexasertib. They show that dampened expression of transcription factor FOXM1 and its target genes protected cells against ...
Hendrika A. Segeren, Kathryn A. Wierenga, Frank M. Riemers, Elsbeth A. van Liere, Bart Westendorp   +4 more
wiley   +1 more source

Spectral Dimensionality Reduction [PDF]

In this paper, we study and put under a common framework a number of non-linear dimensionality reduction methods, such as Locally Linear Embedding, Isomap, Laplacian Eigenmaps and kernel PCA, which are based on performing an eigen-decomposition (hence ...
Jean-François Paiement, Marie Ouimet, Nicolas Le Roux, Olivier Delalleau, Pascal Vincent, Yoshua Bengio   +5 more
core  

Detecting Adversarial Examples through Nonlinear Dimensionality Reduction [PDF]

, 2019
Deep neural networks are vulnerable to adversarial examples, i.e., carefully-perturbed inputs aimed to mislead classification. This work proposes a detection method based on combining non-linear dimensionality reduction and density estimation techniques.
Bacciu, Davide, Biggio, Battista, Crecchi, Francesco   +2 more
core   +1 more source

Reduction of Dimensionality for Classification

, 2017
We present an algorithm for the reduction of dimensionality useful in statistical classification problems where observations from two multivariate normal distributions are discriminated. It is based on Principal Components Analysis and consists of a simultaneous diagonalization of two covariance matrices.
Cuevas Covarrubias,C, RICCOMAGNO, EVA
openaire   +3 more sources

Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value

Molecular Oncology, EarlyView.
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song, Zhe Wang, Guangji Zhang, Jiangxue Hou, Kaiqi Liu, Shuning Wei, Yan Li, Chunlin Zhou, Dong Lin, Min Wang, Hui Wei, Jianxiang Wang, Tao Cheng, Yingchang Mi   +13 more
wiley   +1 more source

Two-Stage Dimensionality Reduction for Social Media Engagement Classification

Applied Sciences
The high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will ...
Jose Luis Vieira Sobrinho, Flavio Henrique Teles Vieira, Alisson Assis Cardoso   +2 more
doaj   +1 more source

A Review, Framework and R toolkit for Exploring, Evaluating, and Comparing Visualizations [PDF]

arXiv, 2019
This paper gives a review and synthesis of methods of evaluating dimensionality reduction techniques. Particular attention is paid to rank-order neighborhood evaluation metrics. A framework is created for exploring dimensionality reduction quality through visualization. An associated toolkit is implemented in R. The toolkit includes scatter plots, heat
arxiv  

Plasma lipidomic and metabolomic profiles in high‐grade glioma patients before and after 72‐h presurgery water‐only fasting

Molecular Oncology, EarlyView.
Presurgery 72‐h fasting in GB patients leads to adaptations of plasma lipids and polar metabolites. Fasting reduces lysophosphatidylcholines and increases free fatty acids, shifts triglycerides toward long‐chain TGs and increases branched‐chain amino acids, alpha aminobutyric acid, and uric acid.
Iris Divé, Lisa Hahnefeld, Katharina J. Wenger, Donat Kögel, Joachim Steinbach, Gerd Geisslinger, Michael W. Ronellenfitsch, Irmgard Tegeder   +7 more
wiley   +1 more source