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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 6501–6525 of 9051 papers

TitleStatusHype
Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network—0
Determinantal consensus clustering—0
Bacteriophage classification for assembled contigs using Graph Convolutional NetworkCode1
DOA Estimation with Non-Uniform Linear Arrays: A Phase-Difference Projection ApproachCode1
A Simple Cooperative Diversity Method Based on Deep-Learning-Aided Relay Selection—0
Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling—0
Co-Mixup: Saliency Guided Joint Mixup with Supermodular DiversityCode1
Diversity-Robust Acoustic Feature Signatures Based on Multiscale Fractal Dimension for Similarity Search of Environmental Sounds—0
Diversification in Session-based News Recommender SystemsCode0
A Supervised Segmentation Network for Hyperspectral Image Classification—0
Neural Data Augmentation via Example ExtrapolationCode0
Neural representation and generation for RNA secondary structures—0
A reproducibility study of "Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space"—0
Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language ModelsCode1
Underwater Image Enhancement via Learning Water Type Desensitized RepresentationsCode1
[Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency?Code0
Infant Cry Classification with Graph Convolutional Networks—0
Introduction of a novel word embedding approach based on technology labels extracted from patent data—0
Towards Imperceptible Query-limited Adversarial Attacks with Perceptual Feature Fidelity Loss—0
MultiRocket: Multiple pooling operators and transformations for fast and effective time series classificationCode1
Niching Diversity Estimation for Multi-modal Multi-objective Optimization—0
Neural networks for semantic segmentation of historical city maps: Cross-cultural performance and the impact of figurative diversity—0
No-Regret Caching via Online Mirror Descent—0
Jane Jacobs in the Sky: Predicting Urban Vitality with Open Satellite Data—0
Perceptions of Diversity in Electronic Music: the Impact of Listener, Artist, and Track CharacteristicsCode0
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