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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 2676–2700 of 9051 papers

TitleStatusHype
A Note on the Global Convergence of Multilayer Neural Networks in the Mean Field Regime—0
A note on the Diversity Owen values—0
Advancing the Arabic WordNet: Elevating Content Quality—0
Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite—0
Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection—0
A Note on Species Richness and the Variance of Epidemic Severity—0
Camouflaged Chinese Spam Content Detection with Semi-supervised Generative Active Learning—0
Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars—0
A comparative study of universal quantum computing models: towards a physical unification—0
An Optimism-based Approach to Online Evaluation of Generative Models—0
CameraPose: Weakly-Supervised Monocular 3D Human Pose Estimation by Leveraging In-the-wild 2D Annotations—0
A Comparative Study of Transfer Learning for Emotion Recognition using CNN and Modified VGG16 Models—0
Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation—0
3D Shape Generation: A Survey—0
Cambrian Explosion Algorithm for Multi-Objective Association Rules Mining—0
A Nonlocal InSAR Filter for High-Resolution DEM Generation from TanDEM-X Interferograms—0
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters—0
A Nonlinear African Vulture Optimization Algorithm Combining Henon Chaotic Mapping Theory and Reverse Learning Competition Strategy—0
Effective Data Augmentation Approaches to End-to-End Task-Oriented Dialogue—0
Generalization through Diversity: Improving Unsupervised Environment Design—0
Effective Visualization and Analysis of Recommender Systems—0
Call for Action: towards the next generation of symbolic regression benchmark—0
An Online Approach to Dynamic Channel Access and Transmission Scheduling—0
AnomalyPainter: Vision-Language-Diffusion Synergy for Zero-Shot Realistic and Diverse Industrial Anomaly Synthesis—0
Calibrated Vehicle Paint Signatures for Simulating Hyperspectral Imagery—0
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