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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 6926–6950 of 9051 papers

TitleStatusHype
Determinantal Point Process as an alternative to NMSCode0
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of ModelsCode1
Large Scale Photometric Bundle Adjustment—0
Towards Comprehensive Recommender Systems: Time-Aware UnifiedcRecommendations Based on Listwise Ranking of Implicit Cross-Network Data—0
End-to-End 3D Multi-Object Tracking and Trajectory Forecasting—0
CnGAN: Generative Adversarial Networks for Cross-network user preference generation for non-overlapped usersCode0
Exploring the use of Time-Dependent Cross-Network Information for Personalized Recommendations—0
LSTM Networks for Online Cross-Network Recommendations—0
Short-Packet Communications for MIMO NOMA Systems over Nakagami-m Fading: BLER and Minimum Blocklength Analysis—0
Study of Intelligent Reflective Surface Assisted Communications with One-bit Phase Adjustments—0
Applications of BERT Based Sequence Tagging Models on Chinese Medical Text Attributes Extraction—0
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data with Diversity In Memory—0
Few-Shot Learning with Intra-Class Knowledge Transfer—0
On Nondeterminism and Instability in Optimizing Neural Networks—0
Don't Change Me! User-Controllable Selective Paraphrase Generation—0
Spatial--spectral FFPNet: Attention-Based Pyramid Network for Segmentation and Classification of Remote Sensing Images—0
Expressing Diverse Human Driving Behavior with Probabilistic Rewards and Online Inference—0
Combinatorial diversity metrics for the analysis of policy processes—0
No-reference Screen Content Image Quality Assessment with Unsupervised Domain Adaptation—0
MEANTIME: Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential RecommendationCode1
Fingerprinting Search Keywords over HTTPS at Scale—0
Image Pre-processing on NumtaDB for Bengali Handwritten Digit Recognition—0
Dataset Bias in Few-shot Image Recognition—0
Generative Design by Reinforcement Learning: Enhancing the Diversity of Topology Optimization Designs—0
MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG—0
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