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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 7376–7400 of 9051 papers

TitleStatusHype
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors—0
Anytime Inference with Distilled Hierarchical Neural EnsemblesCode0
Scaling MAP-Elites to Deep NeuroevolutionCode1
LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation—0
Iterative Averaging in the Quest for Best Test Error—0
Learning Texture Invariant Representation for Domain Adaptation of Semantic SegmentationCode1
The Data Science Fire Next Time: Innovative strategies for mentoring in data science—0
Differential Evolution with Individuals Redistribution for Real Parameter Single Objective Optimization—0
Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene GraphsCode1
Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS -- a collection of Technical Notes Part 1—0
Using a thousand optimization tasks to learn hyperparameter search strategies—0
Analysis of diversity-accuracy tradeoff in image captioningCode1
SkinAugment: Auto-Encoding Speaker Conversions for Automatic Speech TranslationCode0
MNN: A Universal and Efficient Inference EngineCode3
PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse DesignsCode1
MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identificationCode0
Forming Diverse Teams from Sequentially Arriving People—0
Diversity-Based Generalization for Unsupervised Text Classification under Domain ShiftCode0
Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective—0
PointAugment: an Auto-Augmentation Framework for Point Cloud ClassificationCode1
Reliable Fidelity and Diversity Metrics for Generative ModelsCode1
DotFAN: A Domain-transferred Face Augmentation Network for Pose and Illumination Invariant Face Recognition—0
Shared optical wireless cells for in-cabin aircraft links—0
Indicator & crowding Distance-Based Evolutionary Algorithm for Combined Heat and Power Economic Emission Dispatch—0
Towards Robust and Reproducible Active Learning Using Neural NetworksCode1
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