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Generalization
Generalization is a broad term that has been described as an individual’s responding to novel stimuli (i.e., stimulus generalization), novel...
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Improving Classifier Generalization Real-Time Machine Learning based Applications
This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight...
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The Evolution from “I think it plus three” Towards “I think it is always plus three.” Transition from Arithmetic Generalization to Algebraic Generalization
This paper is part of broader research being conducted in the area of algebraic thinking in primary education. Our general research objective was to...
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Generalization and Maintenance
Generalization and maintenance is a key tenet to our work as behavioral practitioners. This is highlighted in our work with children with autism...
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Causal Domain Generalization
In the digital age, where machine learning models are ubiquitous, these models tend to rely on several assumptions to achieve high accuracy. The...
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Adversarial data splitting for domain generalization
Domain generalization aims to learn a model that is generalizable to an unseen target domain, which is a fundamental and challenging task in machine...
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Understanding quantum machine learning also requires rethinking generalization
Quantum machine learning models have shown successful generalization performance even when trained with few data. In this work, through systematic...
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The Mechanics of Generalization
This chapter outlines the inner workings of generalization and formally derives much of the ideas presented in the previous chapters. This is done by...
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Strong generalization in quantum neural networks
Generalization is an important feature of neural networks (Nns) as it indicates their ability to predict new and unknown data. However, classical Nns...
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The impact of emotional valence on generalization gradients
Generalization enables individuals to respond to novel stimuli based on previous experiences. The degree to which organisms respond is determined by...
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A taxonomy and review of generalization research in NLP
The ability to generalize well is one of the primary desiderata for models of natural language processing (NLP), but what ‘good generalization’...
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Automated Map Generalization: Emerging Techniques and New Trends (Editorial)
Automated map generalization has been a major area of research for decades but has still not reached maturity. Besides the needs for more adaptive...
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Secure attachment priming inhibits the generalization of conditioned fear
BackgroundFear overgeneralization constitutes a susceptibility factor contributing to the development and maintenance of anxiety spectrum disorders....
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Organizing memories for generalization in complementary learning systems
Memorization and generalization are complementary cognitive processes that jointly promote adaptive behavior. For example, animals should memorize...
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Generalization in Transfer Learning
While fine-tuning and domain adaptation focus on the performance on the target domain, we discuss the generalization of transfer learning in this...
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Stimulus variability improves generalization following response inhibition training
The present study examined the effect of stimulus variability and practice order on generalization to novel stimuli following a single session of...
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Multidimensional specialization and generalization are pervasive in soil prokaryotes
Habitat specialization underpins biological processes from species distributions to speciation. However, organisms are often described as specialists...
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The effect of typicality training on costly safety behavior generalization
Background and objectivesTypicality asymmetry in generalization refers to enhanced fear generalization when trained with typical compared to atypical...
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Out-of-distribution generalization for learning quantum dynamics
Generalization bounds are a critical tool to assess the training data requirements of Quantum Machine Learning (QML). Recent work has established...
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Visual representations with texts domain generalization for semantic segmentation
At present, Domain generalization for semantic segmentation relying on deep neural networks has made little progress. Most of the current methods are...
