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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 6051–6075 of 9051 papers

TitleStatusHype
A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems—0
Predicting the diversity of early epidemic spread on networks—0
Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis TransferCode1
Keiki: Towards Realistic Danmaku Generation via Sequential GANsCode1
FBC-GAN: Diverse and Flexible Image Synthesis via Foreground-Background Composition—0
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization—0
Comparing PCG metrics with Human Evaluation in Minecraft Settlement Generation—0
"Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?Code0
Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes—0
The Price of Diversity—0
Diversity as a By-Product: Goal-oriented Language Generation Leads to Linguistic Variation—0
Effective Social Chatbot Strategies for Increasing User Initiative—0
Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with ExplainabilityCode0
An Investigation of the (In)effectiveness of Counterfactually Augmented DataCode0
Phylogenetic Diversity Rankings in the Face of Extinctions: the Robustness of the Fair Proportion Index—0
Controllable Open-ended Question Generation with A New Question Type OntologyCode1
Improving Human Motion Prediction Through Continual Learning—0
A Weather-Dependent Hybrid RF/FSO Satellite Communication for Improved Power Efficiency—0
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning—0
ResViT: Residual vision transformers for multi-modal medical image synthesisCode1
Ethical AI-Powered Regression Test Selection—0
Multimodal Shape Completion via IMLE—0
A Diverse Corpus for Evaluating and Developing English Math Word Problem SolversCode1
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros StudyCode1
Augmented Shortcuts for Vision TransformersCode0
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