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Stochastic Processes

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A universal deep learning approach for modeling the flow of patients under different severities.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The Accident and Emergency Department (A&ED) is the frontline for providing emergency care in hospitals. Unfortunately, relative A&ED resources have failed to keep up with continuously increasing demand in recent years, whic...

Stochastic spike synchronization in a small-world neural network with spike-timing-dependent plasticity.

Neural networks : the official journal of the International Neural Network Society
We consider the Watts-Strogatz small-world network (SWN) consisting of subthreshold neurons which exhibit noise-induced spikings. This neuronal network has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). ...

Autonomous dynamic obstacle avoidance for bacteria-powered microrobots (BPMs) with modified vector field histogram.

PloS one
In order to broaden the use of microrobots in practical fields, autonomous control algorithms such as obstacle avoidance must be further developed. However, most previous studies of microrobots used manual motion control to navigate past tight spaces...

ASD+M: Automatic parameter tuning in stochastic optimization and on-line learning.

Neural networks : the official journal of the International Neural Network Society
In this paper the classic momentum algorithm for stochastic optimization is considered. A method is introduced that adjusts coefficients for this algorithm during its operation. The method does not depend on any preliminary knowledge of the optimizat...

Discriminatively Trained Latent Ordinal Model for Video Classification.

IEEE transactions on pattern analysis and machine intelligence
We address the problem of video classification for facial analysis and human action recognition. We propose a novel weakly supervised learning method that models the video as a sequence of automatically mined, discriminative sub-events (e.g., onset a...

Stochastic separation theorems.

Neural networks : the official journal of the International Neural Network Society
The problem of non-iterative one-shot and non-destructive correction of unavoidable mistakes arises in all Artificial Intelligence applications in the real world. Its solution requires robust separation of samples with errors from samples where the s...

Accelerating deep neural network training with inconsistent stochastic gradient descent.

Neural networks : the official journal of the International Neural Network Society
Stochastic Gradient Descent (SGD) updates Convolutional Neural Network (CNN) with a noisy gradient computed from a random batch, and each batch evenly updates the network once in an epoch. This model applies the same training effort to each batch, bu...

Analytical solution of the steady membrane voltage fluctuation caused by a single ion channel.

Physical review. E
An analytical steady-state solution of the stochastic model describing the integrated dynamics of the membrane voltage and the gating of a single channel is presented. The voltage density function experiences bifurcation in the parameter space, and t...

Synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and unbounded delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and unbounded discrete time-varying delays is investigated. By virtue of theories of partial differential equations, inequality methods...

Online cross-validation-based ensemble learning.

Statistics in medicine
Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinit...