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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 5501–5525 of 9051 papers

TitleStatusHype
Supporting the development of Machine Learning for fundamental science in a federated Cloud with the AI_INFN platform—0
SURF: Semantic-level Unsupervised Reward Function for Machine Translation—0
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace—0
Surrogate Fitness Metrics for Interpretable Reinforcement Learning—0
Surveying Facial Recognition Models for Diverse Indian Demographics: A Comparative Analysis on LFW and Custom Dataset—0
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models—0
Surveying the Landscape of Image Captioning Evaluation: A Comprehensive Taxonomy and Novel Ensemble Method—0
Survey of Pseudonymization, Abstractive Summarization & Spell Checker for Hindi and Marathi—0
Sustainable Diversity of Phage-Bacteria Systems—0
SVD: A Large-Scale Short Video Dataset for Near-Duplicate Video Retrieval—0
SVP: Style-Enhanced Vivid Portrait Talking Head Diffusion Model—0
SWAG: A Wrapper Method for Sparse Learning—0
SwaQuAD-24: QA Benchmark Dataset in Swahili—0
Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization—0
Swarm Systems as a Platform for Open-Ended Evolutionary Dynamics—0
SwipeCut: Interactive Segmentation with Diversified Seed Proposals—0
Switch-BERT: Learning to Model Multimodal Interactions by Switching Attention and Input—0
Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks—0
Symmetric and Asymmetric Tendencies in Stable Complex Systems—0
Symmetry-Breaking Augmentations for Ad Hoc Teamwork—0
Symmetry-constrained Rectification Network for Scene Text Recognition—0
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation—0
Symptom Identification for Interpretable Detection of Multiple Mental Disorders—0
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation—0
Synaptic Diversity in ANNs Can Facilitate Faster Learning—0
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