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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 5526–5550 of 9051 papers

TitleStatusHype
Realistic Full-Body Anonymization with Surface-Guided GANsCode1
To miss-attend is to misalign! Residual Self-Attentive Feature Alignment for Adapting Object DetectorsCode1
Variational Stacked Local Attention Networks for Diverse Video Captioning—0
Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection—0
Multi-Objective Diverse Human Motion Prediction With Knowledge Distillation—0
C2AM Loss: Chasing a Better Decision Boundary for Long-Tail Object Detection—0
Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task—0
Rethinking Image Cropping: Exploring Diverse Compositions From Global Views—0
Tencent-MVSE: A Large-Scale Benchmark Dataset for Multi-Modal Video Similarity Evaluation—0
Local Attention Pyramid for Scene Image Generation—0
HybridCR: Weakly-Supervised 3D Point Cloud Semantic Segmentation via Hybrid Contrastive RegularizationCode0
InOut: Diverse Image Outpainting via GAN Inversion—0
Image Disentanglement Autoencoder for Steganography Without EmbeddingCode1
Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning—0
LTP: Lane-Based Trajectory Prediction for Autonomous Driving—0
PoseTrack21: A Dataset for Person Search, Multi-Object Tracking and Multi-Person Pose TrackingCode1
Exploring Effective Data for Surrogate Training Towards Black-Box AttackCode1
Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon ColorizationCode1
A Surrogate-Assisted Controller for Expensive Evolutionary Reinforcement Learning—0
NOMA Computation Over Multi-Access Channels for Multimodal Sensing—0
Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity—0
Frequency-Aware Contrastive Learning for Neural Machine Translation—0
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video RecognitionCode1
Investigating Shifts in GAN Output-Distributions—0
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class AnnealingCode0
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