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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 4651–4675 of 9051 papers

TitleStatusHype
Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic RegressionCode0
Identification of Driving Heterogeneity using Action-chains—0
METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer—0
MUSE: Multi-View Contrastive Learning for Heterophilic Graphs—0
Multilingual Lexical Simplification via Paraphrase GenerationCode0
Exploring Format Consistency for Instruction TuningCode0
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?Code0
EqGAN: Feature Equalization Fusion for Few-shot Image Generation—0
Self-Supervised Visual Acoustic Matching—0
Reconciling the accuracy-diversity trade-off in recommendations—0
Data Augmentation for Neural Machine Translation using Generative Language Model—0
Hybrid Representation-Enhanced Sampling for Bayesian Active Learning in Musculoskeletal Segmentation of Lower ExtremitiesCode0
RPG-Palm: Realistic Pseudo-data Generation for Palmprint Recognition—0
Retinotopy Inspired Brain Encoding Model and the All-for-One Training Recipe—0
Towards Bridging the Digital Language Divide—0
Variability in the local and global composition of human T-cell receptor repertoires during thymic development across cell types and individualsCode0
Diversity and Language Technology: How Techno-Linguistic Bias Can Cause Epistemic Injustice—0
Gaussian Graph with Prototypical Contrastive Learning in E-Commerce Bundle Recommendation—0
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness—0
Improved Solution Search Performance of Constrained MOEA/D Hybridizing Directional Mating and Local Mating—0
Improving Out-of-Distribution Robustness of Classifiers via Generative Interpolation—0
Assessing Intra-class Diversity and Quality of Synthetically Generated Images in a Biomedical and Non-biomedical Setting—0
Implementing Smart Contracts: The case of NFT-rental with pay-per-likeCode0
Accurate RSS-Based Localization Using an Opposition-Based Learning Simulated Annealing Algorithm—0
Offline Diversity Maximization Under Imitation Constraints—0
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