AIMC Topic: Online Systems

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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...

A neural controller for online laser power adjustment during the heat therapy process in the presence of nanoparticles.

Australasian physical & engineering sciences in medicine
The present research evaluated the efficiency of a control approach to control the temperature of a breast tumor mass in the presence of nanoparticles exposed to laser radiation. However, if the radiation is carried out in open loop manner it may res...

Patch Based Multiple Instance Learning Algorithm for Object Tracking.

Computational intelligence and neuroscience
To deal with the problems of illumination changes or pose variations and serious partial occlusion, patch based multiple instance learning (P-MIL) algorithm is proposed. The algorithm divides an object into many blocks. Then, the online MIL algorithm...

Classifier transfer with data selection strategies for online support vector machine classification with class imbalance.

Journal of neural engineering
OBJECTIVE: Classifier transfers usually come with dataset shifts. To overcome dataset shifts in practical applications, we consider the limitations in computational resources in this paper for the adaptation of batch learning algorithms, like the sup...

Comparison of Classifier Architectures for Online Neural Spike Sorting.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce...

Problematic internet use (PIU): Associations with the impulsive-compulsive spectrum. An application of machine learning in psychiatry.

Journal of psychiatric research
Problematic internet use is common, functionally impairing, and in need of further study. Its relationship with obsessive-compulsive and impulsive disorders is unclear. Our objective was to evaluate whether problematic internet use can be predicted f...

Adaptive control of nonlinear system using online error minimum neural networks.

ISA transactions
In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: onlin...

Adaptive Online Sequential ELM for Concept Drift Tackling.

Computational intelligence and neuroscience
A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM...

Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization.

Computational intelligence and neuroscience
By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not cons...

Online Knowledge-Based Model for Big Data Topic Extraction.

Computational intelligence and neuroscience
Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data depende...