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Learning from Incomplete Ratings Using Non-negative Matrix Factorization
TLDR
A non-negativity constraint is enforced in the linear model to ensure that each user’s rating profile can be represented as an additive linear combination of canonical coordinates. Expand
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Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering
TLDR
Instead of constraining the factor matrices of NMF to be nonnegative as existing methods, we propose a novel Fast Nonnegative Matrix Trifactorization (FNMTF) approach to constrain them to be cluster indicator matrices, a special type of nonnegative matrices. Expand
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A surface-based approach for classification of 3D neuroanatomic structures
TLDR
We present a framework for 3D surface object classification that combines a powerful shape description method with suitable pattern classification techniques for classifying 3D neuroanatomic structures. Expand
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Entrapping adversaries for source protection in sensor networks
TLDR
This paper proposes a new cyclic entrapment method (CEM) that protects source locations in sensor networks while adding a comparatively low cost in terms of additional message latency and energy. Expand
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Patient Classification of fMRI Activation Maps
TLDR
The analysis of brain activations using functional magnetic resonance imaging (fMRI) is an active area of neuropsychological research. Expand
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Spherical mapping for processing of 3D closed surfaces
TLDR
This paper presents CALD, a new spherical parameterization algorithm that makes the SPHARM model applicable to general triangle meshes. Expand
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Hippocampal shape analysis: surface-based representation and classification
TLDR
We develop a new framework of salient feature extraction and accurate classification for 3D shape data; (2) detect hippocampal abnormalities in schizophrenia using this technique. Expand
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HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data
TLDR
We developed a novel hybrid approach that combines gene ranking and clustering analysis to select a small set of non-redundant marker genes that are most relevant for the classification task. Expand
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Using singular value decomposition approximation for collaborative filtering
TLDR
We present a novel algorithm that incorporates SVD approximation into the expectation-maximization (EM) procedure to reduce the overall computational cost while maintaining accurate predictions. Expand
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Attack detection in time series for recommender systems
TLDR
We postulate that the distribution of item ratings in time can reveal the presence of a wide range of shilling attacks given reasonable assumptions about their duration. Expand
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