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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

Showing 12761300 of 9051 papers

TitleStatusHype
CompOFA: Compound Once-For-All Networks for Faster Multi-Platform DeploymentCode1
Practical Wide-Angle Portraits Correction with Deep Structured ModelsCode1
Vision Transformers with Patch DiversificationCode1
LGD-GCN: Local and Global Disentangled Graph Convolutional NetworksCode1
Towards Accurate Text-based Image Captioning with Content Diversity ExplorationCode1
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable SimulationCode1
Portfolio Search and Optimization for General Strategy Game-PlayingCode1
Diverse and Specific Clarification Question Generation with KeywordsCode1
SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal ConversationsCode1
Optimal Counterfactual Explanations for Scorecard modellingCode1
Ego-Exo: Transferring Visual Representations from Third-person to First-person VideosCode1
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative LearningCode1
Sentence-Permuted Paragraph GenerationCode1
Aligning Latent and Image Spaces to Connect the UnconnectableCode1
Sparse Attention with Linear UnitsCode1
Few-shot Image Generation via Cross-domain CorrespondenceCode1
Deep Time Series Forecasting with Shape and Temporal CriteriaCode1
Contrastive Syn-to-Real GeneralizationCode1
Extraction of instantaneous frequencies and amplitudes in nonstationary time-series dataCode1
Interpretable Unsupervised Diversity Denoising and Artefact RemovalCode1
Towards Evaluating and Training Verifiably Robust Neural NetworksCode1
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space ShrinkingCode1
Unconstrained Scene Generation with Locally Conditioned Radiance FieldsCode1
Rainbow Memory: Continual Learning with a Memory of Diverse SamplesCode1
Self-supervised Discriminative Feature Learning for Deep Multi-view ClusteringCode1
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