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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 4801–4825 of 9051 papers

TitleStatusHype
Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning—0
Pruning variable selection ensembles—0
Pseudo-positive regularization for deep person re-identification—0
Pseudo-Zernike Based Multi-Pass Automatic Target Recognition From Multi-Channel SAR—0
PSGText: Stroke-Guided Scene Text Editing with PSP Module—0
PSVMA+: Exploring Multi-granularity Semantic-visual Adaption for Generalized Zero-shot Learning—0
PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation—0
PubSE: A Hierarchical Model for Publication Extraction from Academic Homepages—0
Pushing the limits of self-supervised speaker verification using regularized distillation framework—0
PVGRU: Generating Diverse and Relevant Dialogue Responses via Pseudo-Variational Mechanism—0
pyribs: A Bare-Bones Python Library for Quality Diversity Optimization—0
QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models—0
QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration—0
QDGset: A Large Scale Grasping Dataset Generated with Quality-Diversity—0
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML—0
Diversity Policy Gradient for Sample Efficient Quality-Diversity Optimization—0
QoS-Aware 3D Coverage Deployment of UAVs for Internet of Vehicles in Intelligent Transportation—0
Qualitative and Quantitative Analysis of Diversity in Cross-document Coreference Resolution Datasets—0
Qualitative Approaches to Voice UX—0
Qualitative Insights Tool (QualIT): LLM Enhanced Topic Modeling—0
Quality and Diversity in Evolutionary Modular Robotics—0
Quality-Diversity Algorithms Can Provably Be Helpful for Optimization—0
Quality Diversity Evolutionary Learning of Decision Trees—0
Quality-diversity for aesthetic evolution—0
Quality Diversity for Robot Learning: Limitations and Future Directions—0
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