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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 1126–1150 of 9051 papers

TitleStatusHype
An Informative Tracking BenchmarkCode1
Learning Semantic-Aligned Feature Representation for Text-based Person SearchCode1
Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary DetectionCode1
Adversarial Parametric Pose PriorCode1
HIVE: Evaluating the Human Interpretability of Visual ExplanationsCode1
NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationCode1
Make It Move: Controllable Image-to-Video Generation with Text DescriptionsCode1
Texture Reformer: Towards Fast and Universal Interactive Texture TransferCode1
Revisiting Neuron Coverage for DNN Testing: A Layer-Wise and Distribution-Aware CriterionCode1
Controllable Video Captioning with an Exemplar SentenceCode1
Generating Diverse 3D Reconstructions from a Single Occluded Face ImageCode1
VoRTX: Volumetric 3D Reconstruction With Transformers for Voxelwise View Selection and FusionCode1
Profiling Pareto Front With Multi-Objective Stein Variational Gradient DescentCode1
Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum GamesCode1
Few-shot Image Generation with Mixup-based Distance LearningCode1
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive LearningCode1
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image RestorationCode1
Scalable Diverse Model Selection for Accessible Transfer LearningCode1
AlphaGarden: Learning to Autonomously Tend a Polyculture GardenCode1
Towards Active Vision for Action Localization with Reactive Control and Predictive LearningCode1
Functional connectivity ensemble method to enhance BCI performance (FUCONE)Code1
Qimera: Data-free Quantization with Synthetic Boundary Supporting SamplesCode1
Improving Contrastive Learning on Imbalanced Seed Data via Open-World SamplingCode1
PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and ClassificationCode1
The chemical space of terpenes: insights from data science and AICode1
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