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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 7851–7875 of 9051 papers

TitleStatusHype
Illumination Spectrum Estimation for Multispectral Images via Surface Reflectance Modeling and Spatial-Spectral Feature GenerationCode0
Learning Gaze-aware Compositional GANCode0
Illuminating the Space of Beatable Lode Runner Levels Produced By Various Generative Adversarial NetworksCode0
Illuminating the Diversity-Fitness Trade-Off in Black-Box OptimizationCode0
Creative Discovery using QD SearchCode0
Learning Guided Electron Microscopy with Active AcquisitionCode0
IIITT@LT-EDI-EACL2021-Hope Speech Detection: There is always Hope in TransformersCode0
Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and BrowsingCode0
IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian LanguagesCode0
Piloting Diversity and Inclusion Workshops in Artificial Intelligence and Robotics for ChildrenCode0
Analysing domain shift factors between videos and images for object detectionCode0
TeDDi Sample: Text Data Diversity Sample for Language Comparison and Multilingual NLPCode0
IIITK@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion in Tamil , Malayalam and EnglishCode0
Attraction-Repulsion clustering with applications to fairnessCode0
DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal GraphsCode0
CP2M: Clustered-Patch-Mixed Mosaic Augmentation for Aerial Image SegmentationCode0
IDIAP_TIET@LT-EDI-ACL2022 : Hope Speech Detection in Social Media using Contextualized BERT with Attention MechanismCode0
Benchmarking Large Language Model Uncertainty for Prompt OptimizationCode0
PixelNet: Representation of the pixels, by the pixels, and for the pixelsCode0
IDIAP Submission@LT-EDI-ACL2022 : Hope Speech Detection for Equality, Diversity and InclusionCode0
Understanding the Generalization of In-Context Learning in Transformers: An Empirical StudyCode0
Template Matching with Deformable Diversity SimilarityCode0
The Impact of Data Distribution on Q-learning with Function ApproximationCode0
IDIAP Submission@LT-EDI-ACL2022: Homophobia/Transphobia Detection in social media commentsCode0
DynED: Dynamic Ensemble Diversification in Data Stream ClassificationCode0
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