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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 6401–6450 of 9051 papers

TitleStatusHype
MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER—0
SIGMORPHON 2021 Shared Task on Morphological Reinflection: Generalization Across Languages—0
Batch Active Learning at ScaleCode0
Why You Should Try the Real Data for the Scene Text Recognition—0
Estimation of functional diversity and species traits from ecological monitoring data—0
Addressing materials' microstructure diversity using transfer learning—0
CRD-CGAN: Category-Consistent and Relativistic Constraints for Diverse Text-to-Image Generation—0
The loss landscape of deep linear neural networks: a second-order analysis—0
Affinity maturation for an optimal balance between long-term immune coverage and short-term resource constraints—0
Towards Controlled and Diverse Generation of Article Comments—0
A binary variant of gravitational search algorithm and its application to windfarm layout optimization problem—0
MIPE: A Metric Independent Pipeline for Effective Code-Mixed NLG Evaluation—0
Learning Quadruped Locomotion Policies using Logical Rules—0
What are you optimizing for? Aligning Recommender Systems with Human Values—0
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression—0
Effects of a pestilent species on the stability of cyclically dominant species—0
Otimizacao de Redes Neurais atraves de Algoritmos Geneticos Celulares—0
Strong, recent selective sweeps reshape genetic diversity in freshwater bivalve Megalonaias nervosa—0
On the Complexity of Optimising Variants of Phylogenetic Diversity on Phylogenetic Networks—0
Solving Large-Scale Multi-Objective Optimization via Probabilistic Prediction Model—0
RBUE: A ReLU-Based Uncertainty Estimation Method of Deep Neural Networks—0
Variational Topic Inference for Chest X-Ray Report Generation—0
DiRe Committee : Diversity and Representation Constraints in Multiwinner Elections—0
An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms—0
Auditing for Diversity using Representative ExamplesCode0
This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces—0
A Deep Generative Artificial Intelligence system to decipher species coexistence patternsCode0
Statistics of the number of equilibria in random social dilemma evolutionary games with mutation—0
CatVRNN: Generating Category Texts via Multi-task LearningCode0
Prb-GAN: A Probabilistic Framework for GAN Modelling—0
Sparse Personalized Federated LearningCode0
A Simple Reward-free Approach to Constrained Reinforcement Learning—0
Asymptotic analysis of V-BLAST MIMO for coherent optical wireless communications in Gamma-Gamma turbulence—0
Sliding Spectrum Decomposition for Diversified Recommendation—0
Designing Recommender Systems to Depolarize—0
Self-Referential Quality Diversity Through Differential Map-Elites—0
HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks—0
Reinforced Hybrid Genetic Algorithm for the Traveling Salesman Problem—0
Multi-headed Neural Ensemble Search—0
GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network—0
Ensembles of Randomized NNs for Pattern-based Time Series Forecasting—0
Selective Focusing Learning in Conditional GANs—0
A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems—0
FBC-GAN: Diverse and Flexible Image Synthesis via Foreground-Background Composition—0
Predicting the diversity of early epidemic spread on networks—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
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