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Embedding methods have shown promising performance in multilabel prediction, as they are able to discover the label dependence. However, most methods ignore the correlations between the input and output, such that their learned embeddings are not well aligned, which leads to degradation in prediction performance. This paper presents a formulation for multilabel learning, from the perspective of cross-view learning, that explores the correlations between the input and the output. The proposed method, called Co-Embedding (CoE), jointly learns a semantic common subspace and view-specific mappings within one framework. The semantic similarity structure among the embeddings is further preserved, ensuring that close embeddings share similar labels. Additionally, CoE conducts multilabel prediction through the cross-view k nearest neighborhood (kNN) search among the learned embeddings, which significantly reduces computational costs compared with conventional decoding schemes. A hashing-based model, i.e., Co-Hashing (CoH), is further proposed. CoH is based on CoE, and imposes the binary constraint on continuous latent embeddings. CoH aims to generate compact binary representations to improve the prediction efficiency by benefiting from the efficient kNN search of multiple labels in the Hamming space. Extensive experiments on various real-world data sets demonstrate the superiority of the proposed methods over the state of the arts in terms of both prediction accuracy and efficiency.
This article was published in the following journal.
Name: IEEE transactions on neural networks and learning systems
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In Augmented Reality (AR), search performance for outdoor tasks is an important metric for evaluating the success of a large number of AR applications. Users must be able to find content quickly, labe...
Chemical cross-linking combined with mass spectrometry provides a method to study protein structures and interactions. The introduction of cleavable bonds in a cross-linker provides an avenue to decou...
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This study aims to describe in depth the CNS, CNS HIV reservoir and CNS viral rebound in consenting SEARCH 019 subjects prior to, during and after the SEARCH 019 study intervention (VHM + ...
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In this study workers are trying to test the correlation between Hammersmith Infant Neurological Examination and MRI brain/cranial ultrasound with early prediction of neurological developm...
Prediction of recovery from stroke can assist in the planning of impairment-focused rehabilitation. To achieve better prediction for clinical purposes, this study investigated a new predic...
A view of the world and the individual's environment as comprehensible, manageable, and meaningful, claiming that the way people view their life has a positive influence on their health.
The difference between two images on the retina when looking at a visual stimulus. This occurs since the two retinas do not have the same view of the stimulus because of the location of our eyes. Thus the left eye does not get exactly the same view as the right eye.
Predicting the time of OVULATION can be achieved by measuring the preovulatory elevation of ESTRADIOL; LUTEINIZING HORMONE or other hormones in BLOOD or URINE. Accuracy of ovulation prediction depends on the completeness of the hormone profiles, and the ability to determine the preovulatory LH peak.
The status or condition of a person over whom any or all of the powers attaching to the right of ownership are exercised. The slave trade is all acts involved in the capture, acquisition or disposal of persons with intent to reduce them to enslavement; all acts involved in the acquisition of enslaved persons with a view to selling or exchanging them; all acts of disposal by sale or exchange of persons acquired with a view to being sold or exchanged, and, in general, every act of trade or transport of slaves. ( from http://www.ohchr.org/Documents/Publications/slaveryen.pdf accessed 10/18/2012)
The systematic search and discovery of natural substances which may have potential commercial applications.