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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 576–600 of 9051 papers

TitleStatusHype
Diverse Image Generation via Self-Conditioned GANsCode1
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of ModelsCode1
Diverse Image-to-Image Translation via Disentangled RepresentationsCode1
Diversified Adversarial Attacks based on Conjugate Gradient MethodCode1
Diversity Enhanced Active Learning with Strictly Proper Scoring RulesCode1
Diverse Cotraining Makes Strong Semi-Supervised SegmentorCode1
Benchmarking Algorithms for Federated Domain GeneralizationCode1
Diverse Generative Perturbations on Attention Space for Transferable Adversarial AttacksCode1
BeLFusion: Latent Diffusion for Behavior-Driven Human Motion PredictionCode1
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence ModelsCode1
Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline GenerationCode1
Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal AnchorsCode1
Advanced Codebook Design for SCMA-aided NTNs With Randomly Distributed UsersCode1
Diverse and Admissible Trajectory Prediction through Multimodal Context UnderstandingCode1
Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior InferenceCode1
Diverse and Admissible Trajectory Forecasting through Multimodal Context UnderstandingCode1
Diverse and Specific Clarification Question Generation with KeywordsCode1
Diverse Human Motion Prediction via Gumbel-Softmax Sampling from an Auxiliary SpaceCode1
A Doubly Decoupled Network for edge detectionCode1
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity MaximizationCode1
DivClust: Controlling Diversity in Deep ClusteringCode1
Distributed speech separation in spatially unconstrained microphone arraysCode1
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identificationCode1
DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial NetworkCode1
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