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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 6851–6875 of 9051 papers

TitleStatusHype
MODEL&CO: Exoplanet detection in angular differential imaging by learning across multiple observations—0
Model Compression with Generative Adversarial Networks—0
Modeling cell differentiation in neuroblastoma: insights into development, malignancy, and treatment relapse—0
Modeling competitive evolution of multiple languages—0
Modeling Content Creator Incentives on Algorithm-Curated Platforms—0
Modeling Context Words as Regions: An Ordinal Regression Approach to Word Embedding—0
Modeling Cultural Dynamics—0
Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder—0
Modeling Field-level Factor Interactions for Fashion Recommendation—0
Modeling Language Usage and Listener Engagement in Podcasts—0
Modeling Multi-granularity Segmentation for Rare Words in Neural Machine Translation—0
Modeling Semantic Relationship in Multi-turn Conversations with Hierarchical Latent Variables—0
Modeling the Evolution of Networks as Shrinking Structural Diversity—0
Modeling User Selection in Quality Diversity—0
Modelling the Formation of Peer-to-Peer Trading Coalitions and Prosumer Participation Incentives in Transactive Energy Communities—0
Model of human collective decision-making in complex environments—0
Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity—0
ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling—0
Modified CMA-ES Algorithm for Multi-Modal Optimization: Incorporating Niching Strategies and Dynamic Adaptation Mechanism—0
Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification—0
Modified Soft Brood Crossover in Genetic Programming—0
MoDiPO: text-to-motion alignment via AI-feedback-driven Direct Preference Optimization—0
Modular Networks: Learning to Decompose Neural Computation—0
Modulating Language Models with Emotions—0
Modulating transfer between tasks in gradient-based meta-learning—0
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