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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 6526–6550 of 9051 papers

TitleStatusHype
BirdNET: A deep learning solution for avian diversity monitoringCode2
LSOIE: A Large-Scale Dataset for Supervised Open Information ExtractionCode1
On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of micro-PCBsCode0
LS-HDIB: A Large Scale Handwritten Document Image Binarization Dataset—0
Adversarial Text-to-Image Synthesis: A Review—0
Black Feminist Musings on Algorithmic Oppression—0
STAR-RISs: Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surfaces—0
Automatic Preference Based Multi-objective Evolutionary Algorithm on Vehicle Fleet Maintenance Scheduling Optimization—0
A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations—0
Investors Embrace Gender Diversity, Not Female CEOs: The Role of Gender in Startup Fundraising—0
Challenges Encountered in Turkish Natural Language Processing Studies—0
ParaSCI: A Large Scientific Paraphrase Dataset for Longer Paraphrase GenerationCode1
Deep Epidemiological Modeling by Black-box Knowledge Distillation: An Accurate Deep Learning Model for COVID-19—0
Neural-based Modeling for Performance Tuning of Spark Data AnalyticsCode0
Macroscopic Control of Text Generation for Image Captioning—0
Clustering Future Scenarios Based on Predicted Range Maps—0
Illuminating the Space of Beatable Lode Runner Levels Produced By Various Generative Adversarial NetworksCode0
Salient Object Detection via Integrity LearningCode1
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse LearningCode1
Is the Capability approach a useful tool for decision aiding in public policy making?—0
SceneGen: Learning to Generate Realistic Traffic Scenes—0
Binary strings of finite VC dimension—0
DivSwapper: Towards Diversified Patch-based Arbitrary Style Transfer—0
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving—0
Operationalizing Framing to Support Multiperspective Recommendations of Opinion Pieces—0
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