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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 6101–6125 of 9051 papers

TitleStatusHype
Repulsive Deep Ensembles are BayesianCode1
How well do you know your summarization datasets?Code0
Context-aware PolyUNet for Liver and Lesion Segmentation from Abdominal CT Images—0
Ensemble of ACCDOA- and EINV2-based Systems with D3Nets and Impulse Response Simulation for Sound Event Localization and Detection—0
Instance-Optimal Compressed Sensing via Posterior SamplingCode1
Instrumental Variable Estimation for Compositional TreatmentsCode0
Calliar: An Online Handwritten Dataset for Arabic CalligraphyCode1
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic lossCode0
Heterogeneous Multi-task Learning with Expert DiversityCode1
On Stein Variational Neural Network Ensembles—0
Lesion-Aware Transformers for Diabetic Retinopathy Grading—0
Boosting Ensemble Accuracy by Revisiting Ensemble Diversity MetricsCode0
LayoutTransformer: Scene Layout Generation With Conceptual and Spatial DiversityCode1
Transferable Query Selection for Active Domain Adaptation—0
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks—0
Indian Masked Faces in the Wild Dataset—0
FAIR: Fairness-Aware Information Retrieval Evaluation—0
Selecting for Selection: Learning To Balance Adaptive and Diversifying Pressures in Evolutionary Search—0
CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis—0
Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization—0
Simple GNN Regularisation for 3D Molecular Property Prediction & BeyondCode1
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier IntegralsCode0
Toward Diverse Precondition Generation—0
Determinantal Beam Search—0
A Framework to Counteract Suboptimal User-Behaviors in Exploratory Learning Environments: an Application to MOOCs—0
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