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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 6551–6575 of 9051 papers

TitleStatusHype
Policy Space Diversity for Non-Transitive Games—0
Political representation bias in DBpedia and Wikidata as a challenge for downstream processing—0
Political Strategies to Overcome Climate Policy Obstructionism—0
POLYGLOT-NER: Massive Multilingual Named Entity Recognition—0
Polyhedral Conic Classifier for CTR Prediction—0
PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts—0
Accelerating AI and Computer Vision for Satellite Pose Estimation on the Intel Myriad X Embedded SoC—0
Polymorphism in rapidly-changing cyclic environment—0
United in Diversity? Contextual Biases in LLM-Based Predictions of the 2024 European Parliament Elections—0
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization—0
Accelerated Image-Aware Generative Diffusion Modeling—0
Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)—0
Popular News Always Compete for the User's Attention! POPK: Mitigating Popularity Bias via a Temporal-Counterfactual—0
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification—0
Regularized Evolutionary Population-Based Training—0
Population Diversity Leads to Short Running Times of Lexicase Selection—0
Population genetics in microchannels—0
Population size predicts lexical diversity, but so does the mean sea level - why it is important to correctly account for the structure of temporal data—0
Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz—0
A Pattern Discovery Approach to Multivariate Time Series Forecasting—0
PortraitBooth: A Versatile Portrait Model for Fast Identity-preserved Personalization—0
A Path to Simpler Models Starts With Noise—0
Accelerated DC loadflow solver for topology optimization—0
Pose-dIVE: Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification—0
Pose Estimation from Camera Images for Underwater Inspection—0
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