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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 5551–5600 of 9051 papers

TitleStatusHype
Towards Federated Learning on Time-Evolving Heterogeneous Data—0
The Curse of Zero Task Diversity: On the Failure of Transfer Learning to Outperform MAML and their Empirical Equivalence—0
Lyapunov Exponents for Diversity in Differentiable Games—0
LAME: Layout Aware Metadata Extraction Approach for Research Articles—0
Multi-speaker Multi-style Text-to-speech Synthesis With Single-speaker Single-style Training Data Scenarios—0
AI-based Reconstruction for Fast MRI -- A Systematic Review and Meta-analysis—0
Maximum Entropy Population-Based Training for Zero-Shot Human-AI CoordinationCode1
AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion GenerationCode1
Cross-Part Learning for Fine-Grained Image ClassificationCode0
Black-Box Testing of Deep Neural Networks Through Test Case DiversityCode0
Spiral Language Modeling—0
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion ModelsCode2
Effects of discordance between species and gene trees on phylogenetic diversity conservation—0
Turbo-Sim: a generalised generative model with a physical latent space—0
Taming Repetition in Dialogue Generation—0
Hierarchical Cross-Modality Semantic Correlation Learning Model for Multimodal Summarization—0
On the Use of Quality Diversity Algorithms for The Traveling Thief Problem—0
Multi-modal Networks Reveal Patterns of Operational Similarity of Terrorist OrganizationsCode0
Counting and optimising maximum phylogenetic diversity sets—0
Cultural Diversity and Its Impact on Governance—0
Tackling the Generative Learning Trilemma with Denoising Diffusion GANsCode1
Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed ClassificationCode1
Text Classification Models for Form Entity LinkingCode1
An Informative Tracking BenchmarkCode1
GM Score: Incorporating inter-class and intra-class generator diversity, discriminability of disentangled representation, and sample fidelity for evaluating GANsCode0
Statistics of the Effective Massive MIMO Channel in Correlated Rician Fading—0
MAGIC: Multimodal relAtional Graph adversarIal inferenCe for Diverse and Unpaired Text-based Image Captioning—0
Learning Semantic-Aligned Feature Representation for Text-based Person SearchCode1
Makeup216: Logo Recognition with Adversarial Attention Representations—0
Re-ranking With Constraints on Diversified Exposures for Homepage Recommender System—0
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region FittingCode0
The Past as a Stochastic Process—0
Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary DetectionCode1
Multimodal Conditional Image Synthesis with Product-of-Experts GANs—0
Guardian of the Ensembles: Introducing Pairwise Adversarially Robust Loss for Resisting Adversarial Attacks in DNN EnsemblesCode0
Burn After Reading: Online Adaptation for Cross-domain Streaming Data—0
Adversarial Parametric Pose PriorCode1
A systematic approach to random data augmentation on graph neural networks—0
Boosting Deep Ensemble Performance with Hierarchical PruningCode0
VizExtract: Automatic Relation Extraction from Data Visualizations—0
CG-NeRF: Conditional Generative Neural Radiance Fields—0
Deep Surrogate Assisted MAP-Elites for Automated Hearthstone DeckbuildingCode0
Saliency Diversified Deep Ensemble for Robustness to Adversaries—0
Dataset Geography: Mapping Language Data to Language UsersCode0
Unsupervised Learning of Compositional Scene Representations from Multiple Unspecified Viewpoints—0
HIVE: Evaluating the Human Interpretability of Visual ExplanationsCode1
NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationCode1
Make It Move: Controllable Image-to-Video Generation with Text DescriptionsCode1
Texture Reformer: Towards Fast and Universal Interactive Texture TransferCode1
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates—0
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