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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 5276–5300 of 9051 papers

TitleStatusHype
Dynamic Diagnosis of the Progress and Shortcomings of Student Learning using Machine Learning based on Cognitive, Social, and Emotional Features—0
Mitigating Bias in Facial Analysis Systems by Incorporating Label Diversity—0
A Universality-Individuality Integration Model for Dialog Act Classification—0
Hierarchical Text-Conditional Image Generation with CLIP LatentsCode3
Flexible Multiple-Objective Reinforcement Learning for Chip Placement—0
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight SharingCode0
Clinical trial site matching with improved diversity using fair policy learning—0
Population Diversity Leads to Short Running Times of Lexicase Selection—0
Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise AffinityCode1
Hierarchical Quality-Diversity for Online Damage RecoveryCode1
Coevolutionary Pareto Diversity Optimization—0
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes—0
Leveraging massively parallel reporter assays for evolutionary questions—0
Benchmarking Active Learning Strategies for Materials Optimization and Discovery—0
Using Linguistic Typology to Enrich Multilingual Lexicons: the Case of Lexical Gaps in KinshipCode0
Semantic Segmentation for Point Cloud Scenes via Dilated Graph Feature Aggregation and Pyramid Decoders—0
Persona-driven Dominant/Submissive Map (PDSM) Generation for Tutorials—0
Coalescent dynamics of planktonic communities—0
Adaptive Channel Allocation for Robust Differentiable Architecture Search—0
Neuronal diversity can improve machine learning for physics and beyondCode0
Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New BaselineCode1
Hierarchical and Multi-Scale Variational Autoencoder for Diverse and Natural Non-Autoregressive Text-to-Speech—0
DiversiTree: A New Method to Efficiently Compute Diverse Sets of Near-Optimal Solutions to Mixed-Integer Optimization Problems—0
Learning to Walk Autonomously via Reset-Free Quality-Diversity—0
DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single ImageCode2
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