Using the Instance-Based Learning Paradigm to Model Energy-Relevant Occupant Behaviors in Buildings
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DOI: 10.1007/s12559-019-09672-w
Abstract: Human interactive behavior is accountable for most of the variance between the observed and predicted energy consumption of buildings, and is accordingly acknowledged as a major field of research into limiting building-related energy consumption. A… read more here.
Keywords: instance based; based learning; model; energy ... See more keywords
A taxonomic look at instance-based stream classifiers
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DOI: 10.1016/j.neucom.2018.01.062
Abstract: Abstract Large numbers of data streams are today generated in many fields. A key challenge when learning from such streams is the problem of concept drift. Many methods, including many prototype methods, have been proposed… read more here.
Keywords: concept drift; taxonomic look; based stream; instance based ... See more keywords
Evaluation of Instance-Based Learning and Q-Learning Algorithms in Dynamic Environments
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DOI: 10.1109/access.2021.3117855
Abstract: Reinforcement learning is an unsupervised learning algorithm, where learning is based upon feedback from the environment. Prior research has proposed cognitive (e.g., Instance-based Learning or IBL) and statistical (Q-learning) reinforcement learning algorithms. However, an evaluation… read more here.
Keywords: instance based; based learning; ibl algorithm; algorithm ... See more keywords
Instance-Based Feature Pyramid for Visual Object Tracking
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DOI: 10.1109/tcsvt.2021.3113041
Abstract: The deep learning based methods have improved the visual tracking precision significantly. However, the background distraction and the high precise localization remain challenging problems. Despite that some methods have fused the deep and shallow layer… read more here.
Keywords: instance based; deep shallow; based feature; feature ... See more keywords
A Regularization Approach for Instance-Based Superset Label Learning
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DOI: 10.1109/tcyb.2017.2669639
Abstract: Different from the traditional supervised learning in which each training example has only one explicit label, superset label learning (SLL) refers to the problem that a training example can be associated with a set of… read more here.
Keywords: superset label; instance based; training example; regularization ... See more keywords
Prediction of Compressive Strength of Concrete and Rock Using an Elementary Instance-Based Learning Algorithm
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DOI: 10.1155/2021/6658932
Abstract: The use of machine learning techniques to predict material strength is becoming popular. However, not much attention has been paid to instance-based learning (IBL) algorithms. Therefore, in order to predict material strength, as the direct… read more here.
Keywords: strength; based learning; elementary instance; instance based ... See more keywords
A Lower Bound for the Query Phase of Contraction Hierarchies and Hub Labels and a Provably Optimal Instance-Based Schema
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DOI: 10.3390/a14060164
Abstract: We prove a Ω(n) lower bound on the query time for contraction hierarchies (CH) as well as hub labels, two popular speed-up techniques for shortest path routing. Our construction is based on a graph family… read more here.
Keywords: instance based; bound query; lower bound; contraction hierarchies ... See more keywords