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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 8076–8100 of 9051 papers

TitleStatusHype
Genesis of the alpha beta T-cell receptor—0
Taking the Scenic Route: Automatic Exploration for Videogames—0
Observing the Population Dynamics in GE by means of the Intrinsic Dimension—0
Teacher-Student Compression with Generative Adversarial NetworksCode0
Towards Continuous Domain adaptation for Healthcare—0
FaceFeat-GAN: a Two-Stage Approach for Identity-Preserving Face Synthesis—0
Towards Accurate Generative Models of Video: A New Metric & ChallengesCode1
A Wasserstein GAN model with the total variational regularization—0
Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning—0
Ego-Downward and Ambient Video based Person Location Association—0
Diverse Ensemble Evolution: Curriculum Data-Model Marriage—0
Efficient nonmyopic batch active search—0
Toddler-Inspired Visual Object Learning—0
Maximum-Entropy Fine Grained Classification—0
Community structures in allelopathic interaction networks: an eco-evolutionary approach—0
Patterning the insect eye: from stochastic to deterministic mechanisms—0
A new system-wide diversity measure for recommendations with efficient algorithms—0
Are All Training Examples Created Equal? An Empirical Study—0
The Graph-Based Behavior-Aware Recommendation for Interactive NewsCode0
GDPP: Learning Diverse Generations Using Determinantal Point ProcessCode0
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation ModelsCode0
GP-CNAS: Convolutional Neural Network Architecture Search with Genetic Programming—0
GANtruth - an unpaired image-to-image translation method for driving scenarios—0
AI Fairness for People with Disabilities: Point of View—0
InstaNAS: Instance-aware Neural Architecture SearchCode0
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