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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 6626–6650 of 9051 papers

TitleStatusHype
Interactive Speech and Noise Modeling for Speech Enhancement—0
StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke EncodingCode1
FedeRank: User Controlled Feedback with Federated Recommender Systems—0
On the Importance of Diversity in Re-Sampling for Imbalanced Data and Rare Events in Mortality Risk Models—0
A New Many-Objective Evolutionary Algorithm Based on Determinantal Point Processes—0
Policy Manifold Search for Improving Diversity-based Neuroevolution—0
Intrinsic Image Captioning Evaluation—0
Sparse Multi-Family Deep Scattering Network—0
Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-EncodersCode1
Relative Variational Intrinsic Control—0
Fork or Fail: Cycle-Consistent Training with Many-to-One MappingsCode1
Improved StyleGAN Embedding: Where are the Good Latents?Code2
Syntactic representation learning for neural network based TTS with syntactic parse tree traversal—0
C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot FillingCode1
Enhanced species coexistence in Lotka-Volterra competition models due to nonlocal interactions—0
DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector QuantizationCode1
Ensemble Squared: A Meta AutoML System—0
Improving the Fairness of Deep Generative Models without RetrainingCode1
Cost-Based Budget Active Learning for Deep Learning—0
Occupational segregation in a Roy model with composition preferences—0
Promoting Semantics in Multi-objective Genetic Programming based on Decomposition—0
Data InStance Prior (DISP) in Generative Adversarial Networks—0
Quality-Diversity Optimization: a novel branch of stochastic optimizationCode1
IRS-Assisted Massive MIMO-NOMA Networks: Exploiting Wave Polarization—0
Diverse Melody Generation from Chinese Lyrics via Mutual Information Maximization—0
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