Eight years of AutoML: categorisation, review and trends
Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …
applied in a large number of application domains. However, apart from the required …
Deep learning in personalization of cardiovascular stents
Deep learning (DL) application has demonstrated its enormous potential in accomplishing
biomedical tasks, such as vessel segmentation, brain visualization, and speech recognition …
biomedical tasks, such as vessel segmentation, brain visualization, and speech recognition …
Experimental tuning of transport regimes in hyperuniform disordered photonic materials
We present wave transport experiments in hyperuniform disordered arrays of cylinders with
high dielectric permittivity. Using microwaves, we show that the same material can display …
high dielectric permittivity. Using microwaves, we show that the same material can display …
Constraint-based clustering selection
Clustering requires the user to define a distance metric, select a clustering algorithm, and set
the hyperparameters of that algorithm. Getting these right, so that a clustering is obtained …
the hyperparameters of that algorithm. Getting these right, so that a clustering is obtained …
A unified view of density-based methods for semi-supervised clustering and classification
Semi-supervised learning is drawing increasing attention in the era of big data, as the gap
between the abundance of cheap, automatically collected unlabeled data and the scarcity of …
between the abundance of cheap, automatically collected unlabeled data and the scarcity of …
Research proposal content extraction using natural language processing and semi-supervised clustering: a demonstration and comparative analysis
BM Knisely, HH Pavliscsak - Scientometrics, 2023 - Springer
Funding institutions often solicit text-based research proposals to evaluate potential
recipients. Leveraging the information contained in these documents could help institutions …
recipients. Leveraging the information contained in these documents could help institutions …
Redundancies in data and their effect on the evaluation of recommendation systems: A case study on the amazon reviews datasets
A collection of datasets crawled from Amazon,“Amazon reviews”, is popular in the evaluation
of recommendation systems. These datasets, however, contain redundancies (duplicated …
of recommendation systems. These datasets, however, contain redundancies (duplicated …
A bibliographic view on constrained clustering
A keyword search on constrained clustering on Web-of-Science returned just under 3,000
documents. We ran automatic analyses of those, and compiled our own bibliography of 183 …
documents. We ran automatic analyses of those, and compiled our own bibliography of 183 …
Bio-inspired constrained clustering: A case study on aspect-based sentiment analysis
M Qasem - 2018 - mspace.lib.umanitoba.ca
Clustering is an important problem in the era of big data. Exact algorithmic clustering
approaches are not affordable for many real-world applications (RWA), requiring innovative …
approaches are not affordable for many real-world applications (RWA), requiring innovative …
Constrained ant brood clustering algorithm with adaptive radius: A case study on aspect based sentiment analysis
Semi-supervised or constrained clustering refers to clustering data instances in the
presence of very limited supervisory information. Although it has been widely investigated in …
presence of very limited supervisory information. Although it has been widely investigated in …