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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 7451–7475 of 9051 papers

TitleStatusHype
Semi-Supervised Phone Classification using Deep Neural Networks and Stochastic Graph-Based Entropic Regularization—0
A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment—0
A K-means-based Multi-subpopulation Particle Swarm Optimization for Neural Network Ensemble—0
VARGAN: Variance Enforcing Network Enhanced GAN—0
AI's Blind Spots: Geographic Knowledge and Diversity Deficit in Generated Urban Scenario—0
AIR: Unifying Individual and Collective Exploration in Cooperative Multi-Agent Reinforcement Learning—0
Zero-Shot Paraphrase Generation with Multilingual Language Models—0
Sentence embedding with contrastive multi-views learning—0
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires—0
Distributionally-Informed Recommender System Evaluation—0
Sentiment Classification in Swahili Language Using Multilingual BERT—0
Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection—0
SentiRec: Sentiment Diversity-aware Neural News Recommendation—0
WoCE: a framework for clustering ensemble by exploiting the wisdom of Crowds theory—0
AIRIS2 : a Smart Gateway Diversity Algorithm for Very High-Throughput Satellite Systems—0
AI in Support of Diversity and Inclusion—0
A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension—0
Sequence to Sequence Mixture Model for Diverse Machine Translation—0
Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity—0
Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control—0
Sequencing Silicates in the IRS Debris Disk Catalog I: Methodology for Unsupervised Clustering—0
Sequential Condition Evolved Interaction Knowledge Graph for Traditional Chinese Medicine Recommendation—0
Sequential Deformation for Accurate Scene Text Detection—0
AI for All: Operationalising Diversity and Inclusion Requirements for AI Systems—0
Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning—0
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