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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 8801–8825 of 9051 papers

TitleStatusHype
Comparing and Combining Lexicase Selection and Novelty Search—0
Comparative Analysis of Indicators for Multiobjective Diversity Optimization—0
MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder—0
Compacting Deep Neural Networks for Internet of Things: Methods and Applications—0
DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation—0
VoxVietnam: a Large-Scale Multi-Genre Dataset for Vietnamese Speaker Recognition—0
Community structures in allelopathic interaction networks: an eco-evolutionary approach—0
Communities as cliques—0
DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models—0
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch—0
DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model—0
DROP: Dynamics Responses from Human Motion Prior and Projective Dynamics—0
Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication—0
Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators—0
VR.net: A Real-world Dataset for Virtual Reality Motion Sickness Research—0
Dropping diversity of products of large US firms: Models and measures—0
Communication Beyond Transmitting Bits: Semantics-Guided Source and Channel Coding—0
Communicate or Sense? AP Mode Selection in mmWave Cell-Free Massive MIMO-ISAC—0
DSS: A Diverse Sample Selection Method to Preserve Knowledge in Class-Incremental Learning—0
DTSGAN: Learning Dynamic Textures via Spatiotemporal Generative Adversarial Network—0
Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling—0
Dual-Attention Graph Convolutional Network—0
Dual-CNN: A Convolutional language decoder for paragraph image captioning—0
AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification—0
Commonality in Recommender Systems: Evaluating Recommender Systems to Enhance Cultural Citizenship—0
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