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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 7626–7650 of 9051 papers

TitleStatusHype
Anomaly Detection in Video Sequence With Appearance-Motion Correspondence—0
Generating Diverse and Descriptive Image Captions Using Visual Paraphrases—0
MultiSeg: Semantically Meaningful, Scale-Diverse Segmentations From Minimal User Input—0
SVD: A Large-Scale Short Video Dataset for Near-Duplicate Video Retrieval—0
A Large-scale Study of Representation Learning with the Visual Task Adaptation BenchmarkCode0
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples—0
Sub-Architecture Ensemble Pruning in Neural Architecture SearchCode0
Generating Diverse Story Continuations with Controllable Semantics—0
Towards Diverse Paraphrase Generation Using Multi-Class Wasserstein GAN—0
Multi-Head Attention with Diversity for Learning Grounded Multilingual Multimodal Representations—0
Semantic Example Guided Image-to-Image Translation—0
Feature Fusion Detector for Semantic Cognition of Remote Sensing—0
Sampling the "Inverse Set" of a Neuron: An Approach to Understanding Neural Nets—0
Markov Decision Process for Video Generation—0
Galaxy Image Simulation Using Progressive GANs—0
Synergistic Team Composition: A Computational Approach to Foster Diversity in Teams—0
CaptainGAN: Navigate Through Embedding Space For Better Text Generation—0
Omnibus Dropout for Improving The Probabilistic Classification Outputs of ConvNets—0
A Quality-Diversity Controllable GAN for Text Generation—0
Is There Mode Collapse? A Case Study on Face Generation and Its Black-box Calibration—0
BRIDGING ADVERSARIAL SAMPLES AND ADVERSARIAL NETWORKS—0
Sentence embedding with contrastive multi-views learning—0
Deep Hierarchical-Hyperspherical Learning (DH^2L)—0
WiderPerson: A Diverse Dataset for Dense Pedestrian Detection in the Wild—0
Stochastic Conditional Generative Networks with Basis Decomposition—0
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