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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 7801–7825 of 9051 papers

TitleStatusHype
Studying evolution of the primary body axis in vivo and in vitro—0
Studying Retrievability of Publications and Datasets in an Integrated Retrieval System—0
Studying the association of online brand importance with museum visitors: An application of the semantic brand score—0
Study of Feature Importance for Quantum Machine Learning Models—0
Study of Intelligent Reflective Surface Assisted Communications with One-bit Phase Adjustments—0
Study of scaling laws in language families—0
Study on Inter and Intra Speaker Variability in Speaker Recognition—0
Study on Patterns and Effect of Task Diversity in Software Crowdsourcing—0
StyLandGAN: A StyleGAN based Landscape Image Synthesis using Depth-map—0
StyleAugment: Learning Texture De-biased Representations by Style Augmentation without Pre-defined Textures—0
A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations—0
StyleCap: Automatic Speaking-Style Captioning from Speech Based on Speech and Language Self-supervised Learning Models—0
Style-Consistent 3D Indoor Scene Synthesis with Decoupled Objects—0
StyleDiT: A Unified Framework for Diverse Child and Partner Faces Synthesis with Style Latent Diffusion Transformer—0
AFEN: Respiratory Disease Classification using Ensemble Learning—0
AFEC: A Knowledge Graph Capturing Social Intelligence in Casual Conversations—0
StyleGenes: Discrete and Efficient Latent Distributions for GANs—0
StyleHumanCLIP: Text-guided Garment Manipulation for StyleGAN-Human—0
StyleInject: Parameter Efficient Tuning of Text-to-Image Diffusion Models—0
CaliciBoost: Performance-Driven Evaluation of Molecular Representations for Caco-2 Permeability Prediction—0
Subjective Perspectives within Learned Representations Predict High-Impact Innovation—0
A fast density peak clustering based particle swarm optimizer for dynamic optimization—0
A Family of Maximum Margin Criterion for Adaptive Learning—0
A Factuality and Diversity Reconciled Decoding Method for Knowledge-Grounded Dialogue Generation—0
Writing as a testbed for open ended agents—0
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