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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 53765400 of 9051 papers

TitleStatusHype
Annotation Efficient Person Re-Identification with Diverse Cluster-Based Pair Selection0
Language Diversity: Visible to Humans, Exploitable by Machines0
Deep Rectangling for Image Stitching: A Learning BaselineCode2
Pointillism: Accurate 3D bounding box estimation with multi-radars0
Skating-Mixer: Long-Term Sport Audio-Visual Modeling with MLPsCode1
Predicting conversion of mild cognitive impairment to Alzheimer's disease0
Towards Universal Texture Synthesis by Combining Texton Broadcasting with Noise Injection in StyleGAN-2Code1
Teleconnection patterns of different El Niño types revealed by climate network curvature0
Piloting Diversity and Inclusion Workshops in Artificial Intelligence and Robotics for ChildrenCode0
Modeling Field-level Factor Interactions for Fashion Recommendation0
L2CS-Net: Fine-Grained Gaze Estimation in Unconstrained EnvironmentsCode2
Building and curating conversational corpora for diversity-aware language science and technology0
Hierarchical Sketch Induction for Paraphrase GenerationCode1
Diversifying Agent's Behaviors in Interactive Decision Models0
UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translationCode1
Freeform Body Motion Generation from SpeechCode2
EAG: Extract and Generate Multi-way Aligned Corpus for Complete Multi-lingual Neural Machine Translation0
Transfer Dynamics in Emergent Evolutionary Curricula0
Provable and Efficient Continual Representation LearningCode0
Deep Latent-Variable Models for Text Generation0
Monitoring Diversity of AI Conferences: Lessons Learnt and Future Challenges in the DivinAI ProjectCode0
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular ValuesCode1
Biological Sequence Design with GFlowNetsCode1
An Instance Space Analysis of Constrained Multi-Objective Optimization Problems0
Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise0
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