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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 8101–8125 of 9051 papers

TitleStatusHype
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models—0
Deep Learning-Enabled Zero-Touch Device Identification: Mitigating the Impact of Channel Variability Through MIMO Diversity—0
Deep Learning for Asynchronous Massive Access with Data Frame Length Diversity—0
Deep Learning for Ophthalmology: The State-of-the-Art and Future Trends—0
Deep Learning for Ultrasound Speed-of-Sound Reconstruction: Impacts of Training Data Diversity on Stability and Robustness—0
Surveying the Landscape of Image Captioning Evaluation: A Comprehensive Taxonomy and Novel Ensemble Method—0
Deep Learning of Determinantal Point Processes via Proper Spectral Sub-gradient—0
Deep learning on butterfly phenotypes tests evolution's oldest mathematical model—0
Survey of Pseudonymization, Abstractive Summarization & Spell Checker for Hindi and Marathi—0
Deep Modularity Networks with Diversity--Preserving Regularization—0
Deep Negative Correlation Classification—0
Deep Neural Ensemble for Retinal Vessel Segmentation in Fundus Images towards Achieving Label-free Angiography—0
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness—0
DeepNNNER: Applying BLSTM-CNNs and Extended Lexicons to Named Entity Recognition in Tweets—0
Deep Occupancy-Predictive Representations for Autonomous Driving—0
Controlling Character Motions without Observable Driving Source—0
Controlling biases and diversity in diverse image-to-image translation—0
Sustainable Diversity of Phage-Bacteria Systems—0
SVD: A Large-Scale Short Video Dataset for Near-Duplicate Video Retrieval—0
DeepPD: Joint Phase and Object Estimation from Phase Diversity with Neural Calibration of a Deformable Mirror—0
Controlled Randomness Improves the Performance of Transformer Models—0
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties—0
Deep Generative Video Compression—0
Deep Probabilistic Video Compression—0
DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization—0
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