AIMC Topic: Algorithms

Clear Filters Showing 23121 to 23130 of 28713 articles

Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

Neural networks : the official journal of the International Neural Network Society
Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of...

Impact of Noise on a Dynamical System: Prediction and Uncertainties from a Swarm-Optimized Neural Network.

Computational intelligence and neuroscience
An artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term x(t + 6). The performance predi...

Fusing Heterogeneous Features From Stacked Sparse Autoencoder for Histopathological Image Analysis.

IEEE journal of biomedical and health informatics
In the analysis of histopathological images, both holistic (e.g., architecture features) and local appearance features demonstrate excellent performance, while their accuracy may vary dramatically when providing different inputs. This motivates us to...

Rediscovery of Good-Turing estimators via Bayesian nonparametrics.

Biometrics
The problem of estimating discovery probabilities originated in the context of statistical ecology, and in recent years it has become popular due to its frequent appearance in challenging applications arising in genetics, bioinformatics, linguistics,...

Machine learning in burn care and research: A systematic review of the literature.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: To date, there are no reviews on machine learning (ML) in burn care. Considering the growth of ML in medicine and the complexities and challenges of burn care, this review specializes on ML applications in burn care. The objective was to ...

Towards dropout training for convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demons...

idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.

Journal of computational biology : a journal of computational molecular cell biology
Predicting the three-dimensional native structures of protein dimers, a problem known as protein-protein docking, is key to understanding molecular interactions. Docking is a computationally challenging problem due to the diversity of interactions an...

Multistability of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays.

Neural networks : the official journal of the International Neural Network Society
The problem of coexistence and dynamical behaviors of multiple equilibrium points is addressed for a class of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays. By virtue of th...

Learning the Structure of Biomedical Relationships from Unstructured Text.

PLoS computational biology
The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured te...