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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 5551–5600 of 9051 papers

TitleStatusHype
Improving COVID-19 CT Classification of CNNs by Learning Parameter-Efficient Representation—0
r/K selection of GC content in prokaryotes—0
Deep Billboards towards Lossless Real2Sim in Virtual Reality—0
Preserving Fine-Grain Feature Information in Classification via Entropic RegularizationCode0
Learning Omnidirectional Flow in 360-degree Video via Siamese Representation—0
Contrastive Positive Mining for Unsupervised 3D Action Representation Learning—0
DeepGen: Diverse Search Ad Generation and Real-Time Customization—0
Mathematical Modeling Analysis and Optimization of Fungal Diversity Growth—0
Evolutionary bagging for ensemble learningCode0
Communication Beyond Transmitting Bits: Semantics-Guided Source and Channel Coding—0
Rethinking the Evaluation of Unbiased Scene Graph Generation—0
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence—0
Semantic Data Augmentation based Distance Metric Learning for Domain Generalization—0
COMET: Coverage-guided Model Generation For Deep Learning Library TestingCode0
Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship—0
Towards Psychologically-Grounded Dynamic Preference Models—0
Safe Perception -- A Hierarchical Monitor Approach—0
A Deep Generative Model for Feasible and Diverse Population Synthesis—0
Information Gain Sampling for Active Learning in Medical Image Classification—0
INSightR-Net: Interpretable Neural Network for Regression using Similarity-based Comparisons to Prototypical ExamplesCode0
Streaming Algorithms for Diversity Maximization with Fairness ConstraintsCode0
Tackling Neural Architecture Search With Quality Diversity OptimizationCode0
Smoothing Entailment Graphs with Language ModelsCode0
Uncertainty-Driven Action Quality Assessment—0
Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity—0
Graph Inverse Reinforcement Learning from Diverse Videos—0
Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation—0
Diversity Boosted Learning for Domain Generalization with Large Number of Domains—0
Analysis of Quality Diversity Algorithms for the Knapsack Problem—0
Gender In Gender Out: A Closer Look at User Attributes in Context-Aware Recommendation—0
Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem—0
LAD: Language Models as Data for Zero-Shot DialogCode0
Class-Aware Universum Inspired Re-Balance Learning for Long-Tailed Recognition—0
Distribution Learning Based on Evolutionary Algorithm Assisted Deep Neural Networks for Imbalanced Image Classification—0
Exploiting Diversity of Unlabeled Data for Label-Efficient Semi-Supervised Active Learning—0
Domain-invariant Feature Exploration for Domain Generalization—0
Representational Ethical Model Calibration—0
Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification—0
Bugs as Features (Part I): Concepts and Foundations for the Compositional Data Analysis of the Microbiome-Gut-Brain Axis—0
Learning Better Registration to Learn Better Few-Shot Medical Image Segmentation: Authenticity, Diversity, and Robustness—0
Few-shot Image Generation Using Discrete Content Representation—0
BigIssue: A Realistic Bug Localization Benchmark—0
FaceFormer: Scale-aware Blind Face Restoration with Transformers—0
GANzilla: User-Driven Direction Discovery in Generative Adversarial Networks—0
On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution DetectionCode0
Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model—0
D-CBRS: Accounting For Intra-Class Diversity in Continual Learning—0
River Surface Patch-wise Detector Using Mixture Augmentation for Scum-cover-index—0
Diversity-aware social robots meet people: beyond context-aware embodied AI—0
IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-trainingCode0
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