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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 1376–1400 of 9051 papers

TitleStatusHype
Distributed speech separation in spatially unconstrained microphone arraysCode1
Diverse Image Captioning with Context-Object Split Latent SpacesCode1
KLPT – Kurdish Language Processing ToolkitCode1
One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RLCode1
Improving Generalization in Reinforcement Learning with Mixture RegularizationCode1
Promoting High Diversity Ensemble Learning with EnsembleBenchCode1
Synthesizing the Unseen for Zero-shot Object DetectionCode1
Fractal Autoencoders for Feature SelectionCode1
Active Domain Adaptation via Clustering Uncertainty-weighted EmbeddingsCode1
Input-Aware Dynamic Backdoor AttackCode1
Probabilistic Time Series Forecasting with Structured Shape and Temporal DiversityCode1
ATF: Towards Robust Face Alignment via Leveraging Similarity and Diversity across Different DatasetsCode1
Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 NetworkCode1
Token-level Adaptive Training for Neural Machine TranslationCode1
Like hiking? You probably enjoy nature: Persona-grounded Dialog with Commonsense ExpansionsCode1
COMETA: A Corpus for Medical Entity Linking in the Social MediaCode1
Automatic Data Augmentation for 3D Medical Image SegmentationCode1
Are "Undocumented Workers" the Same as "Illegal Aliens"? Disentangling Denotation and Connotation in Vector SpacesCode1
Participatory Research for Low-resourced Machine Translation: A Case Study in African LanguagesCode1
Long-tailed Recognition by Routing Diverse Distribution-Aware ExpertsCode1
BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal TransferCode1
GenAug: Data Augmentation for Finetuning Text GeneratorsCode1
MitoEM Dataset: Large-scale 3D Mitochondria Instance Segmentation from EM ImagesCode1
Deep Color Transfer using Histogram AnalogyCode1
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of EnsemblesCode1
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