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Deeply Learned View-Invariant Features for Cross-View Action Recognition.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 24, 2017
Classifying human actions from varied views is challenging due to huge data variations in different views. The key to this problem is to learn discriminative view-invariant features robust to view variations. In this paper, we address this problem by...
Prediction of crime occurrence from multi-modal data using deep learning.
PloS one
Apr 24, 2017
In recent years, various studies have been conducted on the prediction of crime occurrences. This predictive capability is intended to assist in crime prevention by facilitating effective implementation of police patrols. Previous studies have used d...
A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.
International journal of neural systems
Apr 11, 2017
Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current soluti...
Use of a machine learning framework to predict substance use disorder treatment success.
PloS one
Apr 10, 2017
There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitat...
Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.
Statistics in medicine
Apr 6, 2017
Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency v...
An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications.
PloS one
Apr 3, 2017
This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. I...
A neural joint model for entity and relation extraction from biomedical text.
BMC bioinformatics
Mar 31, 2017
BACKGROUND: Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature e...
Automatic segmentation of liver tumors from multiphase contrast-enhanced CT images based on FCNs.
Artificial intelligence in medicine
Mar 27, 2017
This paper presents a novel, fully automatic approach based on a fully convolutional network (FCN) for segmenting liver tumors from CT images. Specifically, we designed a multi-channel fully convolutional network (MC-FCN) to segment liver tumors from...
Representation learning via Dual-Autoencoder for recommendation.
Neural networks : the official journal of the International Neural Network Society
Mar 27, 2017
Recommendation has provoked vast amount of attention and research in recent decades. Most previous works employ matrix factorization techniques to learn the latent factors of users and items. And many subsequent works consider external information, e...
Exploring Approaches for Detecting Protein Functional Similarity within an Orthology-based Framework.
Scientific reports
Mar 23, 2017
Protein functional similarity based on gene ontology (GO) annotations serves as a powerful tool when comparing proteins on a functional level in applications such as protein-protein interaction prediction, gene prioritization, and disease gene discov...
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