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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 1351–1375 of 9051 papers

TitleStatusHype
C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot FillingCode1
DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector QuantizationCode1
Improving the Fairness of Deep Generative Models without RetrainingCode1
Quality-Diversity Optimization: a novel branch of stochastic optimizationCode1
TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language GenerationCode1
Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient SpaceCode1
Diversity-Guided Multi-Objective Bayesian Optimization With Batch EvaluationsCode1
Probabilistic Time Series Forecasting with Shape and Temporal DiversityCode1
S2FGAN: Semantically Aware Interactive Sketch-to-Face TranslationCode1
Enhancing Diversity in Teacher-Student Networks via Asymmetric branches for Unsupervised Person Re-identificationCode1
TaylorGAN: Neighbor-Augmented Policy Update for Sample-Efficient Natural Language GenerationCode1
An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet SpaceCode1
Rethinking conditional GAN training: An approach using geometrically structured latent manifoldsCode1
TJU-DHD: A Diverse High-Resolution Dataset for Object DetectionCode1
Semi-Supervised Few-Shot Atomic Action RecognitionCode1
A Large-Scale Database for Graph Representation LearningCode1
Ego2Hands: A Dataset for Egocentric Two-hand Segmentation and DetectionCode1
Deep Sketch-Based Modeling: Tips and TricksCode1
Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented GraspingCode1
Testing the Impact of Semantics and Structure on Recommendation Accuracy and DiversityCode1
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier ExamplesCode1
Deep generative selection models of T and B cell receptor repertoires with soNNiaCode1
VEGA: Towards an End-to-End Configurable AutoML PipelineCode1
DNN-based mask estimation for distributed speech enhancement in spatially unconstrained microphone arraysCode1
Conditioned Text Generation with Transfer for Closed-Domain Dialogue SystemsCode1
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