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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 3601–3625 of 9051 papers

TitleStatusHype
Content-Diverse Comparisons improve IQA—0
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES—0
Faster and Smarter AutoAugment: Augmentation Policy Search Based on Dynamic Data-Clustering—0
Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks—0
Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity—0
Fast inverse lithography based on a model-driven block stacking convolutional neural network—0
Fast Re-Optimization via Structural Diversity—0
GeneAvatar: Generic Expression-Aware Volumetric Head Avatar Editing from a Single Image—0
Context-based and Diversity-driven Specificity in Compositional Zero-Shot Learning—0
Fatal errors and misuse of mathematics in the Hong-Page Theorem and Landemore's epistemic argument—0
Fault Detection for Covered Conductors With High-Frequency Voltage Signals: From Local Patterns to Global Features—0
Fault Detection in Mobile Networks Using Diffusion Models—0
FBC-GAN: Diverse and Flexible Image Synthesis via Foreground-Background Composition—0
FCBoost-Net: A Generative Network for Synthesizing Multiple Collocated Outfits via Fashion Compatibility Boosting—0
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning—0
Boost Neural Networks by Checkpoints—0
FDNAS: Improving Data Privacy and Model Diversity in AutoML—0
Feasibility Study on Active Learning of Smart Surrogates for Scientific Simulations—0
A novel multiobjective evolutionary algorithm based on decomposition and multi-reference points strategy—0
Feature Augmentation for Self-supervised Contrastive Learning: A Closer Look—0
GANs with Variational Entropy Regularizers: Applications in Mitigating the Mode-Collapse Issue—0
Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation—0
Diversidade linguística e inclusão digital: desafios para uma ia brasileira—0
Feature-based Evolutionary Diversity Optimization of Discriminating Instances for Chance-constrained Optimization Problems—0
An Improved LSHADE-RSP Algorithm with the Cauchy Perturbation: iLSHADE-RSP—0
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