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Heuristics

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A hybridization of distributed policy and heuristic augmentation for improving federated learning approach.

Neural networks : the official journal of the International Neural Network Society
Modifying the existing models of classifiers' operation is primarily aimed at increasing the effectiveness as well as minimizing the training time. An additional advantage is the ability to quickly implement a given solution to the real needs of the ...

DMPP: Differentiable multi-pruner and predictor for neural network pruning.

Neural networks : the official journal of the International Neural Network Society
Neural network pruning can trim the over-parameterized neural networks effectively by removing a number of network parameters. However, the traditional rule-based approaches always depend on manual experience. Existing heuristic search methods in dis...

Improving work detection by segmentation heuristics pre-training on factory operations video.

PloS one
The measurement of work time for individual tasks by using video has made a significant contribution to a framework for productivity improvement such as value stream mapping (VSM). In the past, the work time has been often measured manually, but this...

Heuristic-based channel selection with enhanced deep learning for heart disease prediction under WBAN.

Computer methods in biomechanics and biomedical engineering
The main intention of this proposal is to design and develop a new heart disease prediction model via WBAN using three stages. The first stage is data aggregation, in which data is scheduled in Time Division Multiple Access manner based on priority l...

Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic Approach.

Sensors (Basel, Switzerland)
False alerts due to misconfigured or compromised intrusion detection systems (IDS) in industrial control system (ICS) networks can lead to severe economic and operational damage. However, research using deep learning to reduce false alerts often requ...

Effective method for detecting error causes from incoherent biological ontologies.

Mathematical biosciences and engineering : MBE
Computing the minimal axiom sets (MinAs) for an unsatisfiable class is an important task in incoherent ontology debugging. Ddebugging ontologies based on patterns (DOBP) is a pattern-based debugging method that uses a set of heuristic strategies base...

Multi-Swarm Algorithm for Extreme Learning Machine Optimization.

Sensors (Basel, Switzerland)
There are many machine learning approaches available and commonly used today, however, the extreme learning machine is appraised as one of the fastest and, additionally, relatively efficient models. Its main benefit is that it is very fast, which mak...

Deepaware: A hybrid deep learning and context-aware heuristics-based model for atrial fibrillation detection.

Computer methods and programs in biomedicine
BACKGROUND: State-of-the-art automatic atrial fibrillation (AF) detection models trained on RR-interval (RRI) features generally produce high performance on standard benchmark electrocardiogram (ECG) AF datasets. These models, however, result in a si...

Something's Fishy About It: How Opinion Congeniality and Explainability Affect Motivated Attribution to Artificial Intelligence Versus Human Comment Moderators.

Cyberpsychology, behavior and social networking
An online experiment ( = 384) examined when and how the identity of the comment moderator (artificial intelligence [AI] vs. human) on a news website affects the extent to which individuals (a) suspect political motives for comment removal and (b) bel...

Chemical identification and indexing in PubMed full-text articles using deep learning and heuristics.

Database : the journal of biological databases and curation
The identification of chemicals in articles has attracted a large interest in the biomedical scientific community, given its importance in drug development research. Most of previous research have focused on PubMed abstracts, and further investigatio...