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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 3426–3450 of 9051 papers

TitleStatusHype
Finding Similar Medical Questions from Question Answering Websites—0
Explicit and Implicit Pattern Relation Analysis for Discovering Actionable Negative Sequences—0
Explicit Diversity Conditions for Effective Question Answer Generation with Large Language Models—0
Diversify and Conquer: Bandits and Diversity for an Enhanced E-commerce Homepage Experience—0
BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity search—0
Diversified Visual Attention Networks for Fine-Grained Object Classification—0
Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection—0
Compositional Zero-Shot Learning via Fine-Grained Dense Feature Composition—0
Exploiting Cross-Lingual Speaker and Phonetic Diversity for Unsupervised Subword Modeling—0
Diversified Texture Synthesis with Feed-forward Networks—0
Exploiting Feature Diversity for Make-up Temporal Video Grounding—0
Exploiting Joint Robustness to Adversarial Perturbations—0
Exploiting Knowledge Distillation for Few-Shot Image Generation—0
An Information-Theoretic Approach for Estimating Scenario Generalization in Crowd Motion Prediction—0
EXPLOITING SEMANTIC COHERENCE TO IMPROVE PREDICTION IN SATELLITE SCENE IMAGE ANALYSIS: APPLICATION TO DISEASE DENSITY ESTIMATION—0
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes—0
Exploiting Spatial-temporal Correlations for Video Anomaly Detection—0
Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning—0
Exploiting Web Images for Weakly Supervised Object Detection—0
Explorable Tone Mapping Operators—0
Exploration and Exploitation in Symbolic Regression using Quality-Diversity and Evolutionary Strategies Algorithms—0
Findings of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion—0
Explorations in an English Poetry Corpus: A Neurocognitive Poetics Perspective—0
Exploratory Data Analysis of Urdu Poetry—0
Diversified Sampling Improves Scaling LLM inference—0
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