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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 3351–3375 of 9051 papers

TitleStatusHype
Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation—0
adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads—0
Comparing heterogeneous visual gestures for measuring the diversity of visual speech signals—0
EVINCE: Optimizing Multi-LLM Dialogues Using Conditional Statistics and Information Theory—0
EVOC: A Computer Model of the Evolution of Culture—0
EvoGPT: Enhancing Test Suite Robustness via LLM-Based Generation and Genetic Optimization—0
FedAlign: Federated Domain Generalization with Cross-Client Feature Alignment—0
Evolutionary Algorithms Simulating Molecular Evolution: A New Field Proposal—0
Comparing Photorealism in Game Engines for Synthetic Maritime Computer Vision Datasets—0
Evolutionary Computation-Assisted Brainwriting for Large-Scale Online Ideation—0
Evolutionary Demographic Algorithms—0
Evolutionary Diversity Optimisation for The Traveling Thief Problem—0
Evolutionary Diversity Optimisation in Constructing Satisfying Assignments—0
Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem—0
Evolutionary Diversity Optimization Using Multi-Objective Indicators—0
Evolutionary Diversity Optimization with Clustering-based Selection for Reinforcement Learning—0
Evolutionary drivers, morphological evolution and diversity dynamics of a surviving mammal clade: cainotherioids at the Eocene--Oligocene transition—0
Evolutionary Dynamic Multi-objective Optimization Via Regression Transfer Learning—0
Evolutionary Dynamic Optimization and Machine Learning—0
Evolutionary features in a minimal physical system: directionality, diversity, selection, growth, inheritance, and adaptation—0
Comparison of various image fusion methods for impervious surface classification from VNREDSat-1—0
Evolutionary Landscape and Management of Population Diversity—0
Evolutionary Multimodal Optimization: A Short Survey—0
Evolutionary Multi-Objective Diversity Optimization—0
FedDAR: Federated Domain-Aware Representation Learning—0
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