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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 8601–8625 of 9051 papers

TitleStatusHype
Snapshot Difference Imaging using Time-of-Flight Sensors—0
Gradient Estimators for Implicit ModelsCode0
Learning to Identify Ambiguous and Misleading News Headlines—0
Ensemble of heterogeneous flexible neural trees using multiobjective genetic programmingCode0
Quality and Diversity Optimization: A Unifying Modular FrameworkCode0
Classification and Representation via Separable Subspaces: Performance Limits and Algorithms—0
Discrete Modeling of Multi-Transmitter Neural Networks with Neuron CompetitionCode0
Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity—0
Query-adaptive Video Summarization via Quality-aware Relevance EstimationCode0
Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s)—0
Topologically Robust 3D Shape Matching via Gradual Deflation and Inflation—0
Active Collaborative Ensemble Tracking—0
Mostly Exploration-Free Algorithms for Contextual BanditsCode0
Action Understanding with Multiple Classes of Actors—0
Genealogical Distance as a Diversity Estimate in Evolutionary Algorithms—0
Pruning variable selection ensembles—0
Diversity driven Attention Model for Query-based Abstractive SummarizationCode0
A Time Series Analysis-Based Forecasting Framework for the Indian Healthcare Sector—0
Ranking with Fairness ConstraintsCode0
Cross-domain Semantic Parsing via ParaphrasingCode0
Understanding Task Design Trade-offs in Crowdsourced Paraphrase Collection—0
Discovering Evolutionary Stepping Stones through Behavior Domination—0
A Search for Improved Performance in Regular Expressions—0
Detecting Visual Relationships with Deep Relational NetworksCode0
Basic Formal Properties of A Relational Model of The Mathematical Theory of Evidence—0
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