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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 4426–4450 of 9051 papers

TitleStatusHype
MotorFactory: A Blender Add-on for Large Dataset Generation of Small Electric Motors—0
A Unified Theory of Diversity in Ensemble LearningCode0
AERF: Adaptive ensemble random fuzzy algorithm for anomaly detection in cloud computing—0
ATM-R: An Adaptive Tradeoff Model with Reference Points for Constrained Multiobjective Evolutionary Optimization—0
Active Learning for Abstractive Text SummarizationCode0
Universal Information Extraction as Unified Semantic Matching—0
Locomotion-Action-Manipulation: Synthesizing Human-Scene Interactions in Complex 3D Environments—0
CameraPose: Weakly-Supervised Monocular 3D Human Pose Estimation by Leveraging In-the-wild 2D Annotations—0
Mask-then-Fill: A Flexible and Effective Data Augmentation Framework for Event Extraction—0
Evaluating Evasion Strategies in Zebrafish Larvae—0
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms—0
Plant species richness prediction from DESIS hyperspectral data: A comparison study on feature extraction procedures and regression models—0
WLD-Reg: A Data-dependent Within-layer Diversity RegularizerCode0
Gender Diversity in Ownership and Firm Innovativeness in Emerging Markets. The Mediating Roles of R&D Investments and External Capital—0
PMT-IQA: Progressive Multi-task Learning for Blind Image Quality AssessmentCode0
Testing High-dimensional Multinomials with Applications to Text Analysis—0
MHEntropy: Entropy Meets Multiple Hypotheses for Pose and Shape RecoveryCode0
Learning with Diversity: Self-Expanded Equalization for Better Generalized Deep Metric Learning—0
Zero-Shot Point Cloud Segmentation by Semantic-Visual Aware SynthesisCode1
Text-Driven Generative Domain Adaptation with Spectral Consistency RegularizationCode0
Building Bridge Across the Time: Disruption and Restoration of Murals In the Wild—0
Both Diverse and Realism Matter: Physical Attribute and Style Alignment for Rainy Image Generation—0
SiLK: Simple Learned Keypoints—0
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Self-Evolved Dynamic Expansion Model for Task-Free Continual LearningCode0
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