Results 101 to 110 of about 141,001 (306)
Dimensionality reduction on vector spaces using complex random matrices [PDF]
reservedIn this thesis we present part of a wider work regarding dimensionality reduction on the Euclidean space. Specifically we focus on finding concentration bounds for sums of Rademacher Chaoses.
MORETTI, SIMONE
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Tailored Scalable Dimensionality Reduction [PDF]
, 2018 Although there is a rich literature on scalable methods for dimensionality reduction, the focus has been on widely applicable approaches which, in certain applications, are far from optimal or not even applicable.
van den Boom, Willem
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Dimensionality Reduction Using Factor Analysis [PDF]
, 2006 In many pattern recognition applications, a large number of features are extracted in order to ensure an accurate classification of unknown classes. One way to solve the problems of high dimensions is to first reduce the dimensionality of the data to a ...
Khosla, Nitin
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Interpreting the effects of DNA polymerase variants at the structural level
Molecular Oncology, EarlyView.Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi +7 more
wiley +1 more source
Dimensionality Reduction via Multiple Locality-Constrained Graph Optimization
IEEE Access, 2018 In recent years, graph-based dimensionality reduction methods became increasingly more significant since they have been successfully applied in various computer vision and machine learning problems.
Caixia Zheng +6 more
doaj +1 more source
Robust dimensionality reduction for interferometric imaging of Cygnus A [PDF]
Extremely high data rates expected in next-generation radio interferometers necessitate a fast and robust way to process measurements in a big data context.
Thiran, Jean-Philippe +3 more
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Multilabel dimensionality reduction via dependence maximization [PDF]
, 2010 Multilabel learning deals with data associated with multiple labels simultaneously. Like other data mining and machine learning tasks, multilabel learning also suffers from the curse of dimensionality . Dimensionality
Zhi-Hua Zhou, Yin Zhang
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Dimensionality Reduction Algorithms on High Dimensional Datasets
Emitter: International Journal of Engineering Technology, 2014 Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicatedespecially when the number of possible ...
Iwan Syarif
doaj +3 more sources
Molecular Oncology, EarlyView.Ixazomib inhibits proteasome‐mediated degradation of topoisomerase I induced by irinotecan, thereby restoring drug sensitivity and promoting tumor cell death in colorectal cancer. Irinotecan, a topoisomerase I (topoI) inhibitor, is widely used for colorectal cancer, but resistance remains a major clinical challenge.
Yuho Ebata +10 more
wiley +1 more source
Dimensionality Reduction [PDF]
, 2008 Dimensionality reduction studies methods that effectively reduce data dimensionality for efficient data process-ing tasks such as pattern recognition, machine learning, text retrieval, and data mining.
Huan Liu, Manoranjan Dash
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