Results 61 to 70 of about 2,532,241 (263)
Random sampling of bandlimited signals on graphs [PDF]
, 2015 We study the problem of sampling k-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random.
Gribonval, Rémi +3 more
core +1 more source
Weighted Random Walk Sampling for Multi-Relational Recommendation
, 2017 In the information overloaded web, personalized recommender systems are essential tools to help users find most relevant information. The most heavily-used recommendation frameworks assume user interactions that are characterized by a single relation ...
Burke Robin D. +3 more
core +1 more source
Molecular Oncology, EarlyView.Detection of extrachromosomal circular DNA (eccDNA) in plasma samples from EGFR‐mutated non‐small cell lung cancer patients. Plasma was collected before and during treatment with the EGFR‐tyrosine kinase inhibitor osimertinib. Plasma eccDNA was detected in all cancer samples, and the presence of the EGFR gene on eccDNA serves as a potential biomarker ...
Simone Stensgaard +5 more
wiley +1 more source
Analysis of Crowdsourced Sampling Strategies for HodgeRank with Sparse Random Graphs
, 2016 Crowdsourcing platforms are now extensively used for conducting subjective pairwise comparison studies. In this setting, a pairwise comparison dataset is typically gathered via random sampling, either \emph{with} or \emph{without} replacement.
Osting, Braxton +3 more
core +3 more sources
Molecular Oncology, EarlyView.We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck +12 more
wiley +1 more source
Inverse functions for Monte Carlo simulations with applications to hitting time distributions
Engineering Reports, 2021 Random sampling is a ubiquitous tool in simulations and modeling in a variety of applications. There are efficient algorithms for several known distributions, but in general, one must resort to computing or approximating the inverse of the distributions ...
Avishai Ben‐David, Raghu Raghavan
doaj +1 more source
Molecular Oncology, EarlyView.We developed a cost‐effective methylation‐specific droplet digital PCR multiplex assay containing tissue‐conserved and tumor‐specific methylation markers. The assay can detect circulating tumor DNA with high accuracy in patients with localized and metastatic colorectal cancer.
Luisa Matos do Canto +8 more
wiley +1 more source
Fast Number Theoretic Transform for Ring-LWE on 8-bit AVR Embedded Processor
Sensors, 2020 In this paper, we optimized Number Theoretic Transform (NTT) and random sampling operations on low-end 8-bit AVR microcontrollers. We focused on the optimized modular multiplication with secure countermeasure (i.e., constant timing), which ensures high ...
Hwajeong Seo +6 more
doaj +1 more source
Random Walk Sampling for Big Data over Networks
, 2017 It has been shown recently that graph signals with small total variation can be accurately recovered from only few samples if the sampling set satisfies a certain condition, referred to as the network nullspace property. Based on this recovery condition,
Basirian, Saeed, Jung, Alexander
core +1 more source
Next‐generation proteomics improves lung cancer risk prediction
Molecular Oncology, EarlyView.This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj +4 more
wiley +1 more source