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Lazy multi-label learning algorithms based on mutuality strategies
(SpringerDordrecht, 2015-12)
Lazy multi-label learning algorithms have become an important research topic within the multi-label community. These algorithms usually consider the set of standard k-Nearest Neighbors of a new instance to predict its ...
An efficient algorithm for approximated self-similarity joins in metric spaces
(Elsevier, 2020)
Similarity join is a key operation in metric databases. It retrieves all pairs of elements that are similar. Solving such a problem usually requires comparing every pair of objects of the datasets, even when indexing and ...
Exotic lagomorph may influence eagle abundances and breeding spatial aggregations: A field study and meta- analysis on the nearest neighbor distance
(PeerJ, 2018-05-10)
The introduction of alien species could be changing food source composition, ultimately restructuring demography and spatial distribution of native communities. In Argentine Patagonia, the exotic European hare has one of ...
Chaotic Synchronization in Nearest-Neighbor Coupled Networks of 3D CNNs
(Universidad Nacional Autónoma de México (UNAM), 2013)
Comment on computational model for predicting experimental rna and dna nearest-neighbor free energy rankings
(AMERICAN CHEMICAL SOCIETY, 2012)
Near neighbor searching with K nearest references
(Elsevier, 2015)
Proximity searching is the problem of retrieving,from a given database, those objects
closest to a query.To avoid exhaustive searching,data structures called indexes are builton
the database prior to serving queries.The ...
Compact distance histogram: a novel structure to boost k-nearest neighbor queries
(University of CaliforniaAssociation for Computing Machinery - ACMLa Jolla, 2015-06)
The k-Nearest Neighbor query (k-NNq) is one of the most useful similarity queries. Elaborated k-NNq algorithms depend on an initial radius to prune regions of the search space that cannot contribute to the answer. Therefore, ...
Face Recognition with Local Binary Patterns, Spatial Pyramid Histograms and Naive Bayes Nearest Neighbor Classification
(IEEE, 2009)
Face recognition algorithms commonly assume that face images are well aligned and have a similar pose -- yet in many practical applications it is impossible to meet these conditions. Therefore extending face recognition ...