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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 5451–5475 of 9051 papers

TitleStatusHype
A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications—0
Tracking of plus-ends reveals microtubule functional diversity in different cell types—0
Mean and Variance of Phylogenetic Trees—0
A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules—0
Measures of Information Reflect Memorization Patterns—0
Measuring Adversarial Datasets—0
Measuring and Improving Semantic Diversity of Dialogue Generation—0
Tracking Sports Players with Context-Conditioned Motion Models—0
Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship—0
A Unifying View of Explicit and Implicit Feature Maps of Graph Kernels—0
Measuring Diversity: Axioms and Challenges—0
Measuring Diversity in Co-creative Image Generation—0
Measuring Diversity in Heterogeneous Information Networks—0
A Unifying Information-theoretic Perspective on Evaluating Generative Models—0
Measuring Diversity of Artificial Intelligence Conferences—0
Measuring Diversity of Game Scenarios—0
Measuring diversity of synthetic prompts and data generated with fine-grained persona prompting—0
Measuring Feature Diversity in Native Language Identification—0
Measuring GAN Training in Real Time—0
Measuring Grammatical Diversity from Small Corpora: Derivational Entropy Rates, Mean Length of Utterances, and Annotation Invariance—0
Measuring HLT Research Equality of European Languages—0
Measuring Integrated Information: Comparison of Candidate Measures in Theory and Simulation—0
Measuring Lexical Diversity in Texts: The Twofold Length Problem—0
Measuring Linguistic Diversity During COVID-19—0
A unified view of generative models for networks: models, methods, opportunities, and challenges—0
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