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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 1101–1125 of 9051 papers

TitleStatusHype
Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill DiversityCode1
TIML: Task-Informed Meta-Learning for AgricultureCode1
Lipschitz-constrained Unsupervised Skill DiscoveryCode1
CIC: Contrastive Intrinsic Control for Unsupervised Skill DiscoveryCode1
NeuralTailor: Reconstructing Sewing Pattern Structures from 3D Point Clouds of GarmentsCode1
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement LearningCode1
Variational Neural Cellular AutomataCode1
Any-Play: An Intrinsic Augmentation for Zero-Shot CoordinationCode1
You Only Cut Once: Boosting Data Augmentation with a Single CutCode1
Variational Model Inversion AttacksCode1
Towards Objective Metrics for Procedurally Generated Video Game LevelsCode1
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset CreationCode1
Tailor Versatile Multi-modal Learning for Multi-label Emotion RecognitionCode1
Realistic Full-Body Anonymization with Surface-Guided GANsCode1
To miss-attend is to misalign! Residual Self-Attentive Feature Alignment for Adapting Object DetectorsCode1
Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon ColorizationCode1
Exploring Effective Data for Surrogate Training Towards Black-Box AttackCode1
Image Disentanglement Autoencoder for Steganography Without EmbeddingCode1
PoseTrack21: A Dataset for Person Search, Multi-Object Tracking and Multi-Person Pose TrackingCode1
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video RecognitionCode1
Maximum Entropy Population-Based Training for Zero-Shot Human-AI CoordinationCode1
AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion GenerationCode1
Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed ClassificationCode1
Tackling the Generative Learning Trilemma with Denoising Diffusion GANsCode1
Text Classification Models for Form Entity LinkingCode1
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