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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 3701–3725 of 9051 papers

TitleStatusHype
A Taxonomy of Adaptive Traffic Signal Control—0
Path Shadowing Monte-CarloCode1
TSMD: A Database for Static Color Mesh Quality Assessment Study—0
Are Easy Data Easy (for K-Means)—0
Feature-aware conditional GAN for category text generation—0
Wasserstein Diversity-Enriched Regularizer for Hierarchical Reinforcement Learning—0
A Novel Cross-Perturbation for Single Domain Generalization—0
ADS-Cap: A Framework for Accurate and Diverse Stylized Captioning with Unpaired Stylistic CorporaCode0
Phase Diverse Phase Retrieval for Microscopy: Comparison of Gaussian and Poisson ApproachesCode0
Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessment—0
The Algonauts Project 2023 Challenge: UARK-UAlbany Team SolutionCode0
Human-M3: A Multi-view Multi-modal Dataset for 3D Human Pose Estimation in Outdoor ScenesCode1
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness—0
FLatten Transformer: Vision Transformer using Focused Linear AttentionCode2
BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel OptimizationCode0
Deep Image Harmonization with Learnable AugmentationCode1
Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic RegressionCode0
Identification of Driving Heterogeneity using Action-chains—0
MUSE: Multi-View Contrastive Learning for Heterophilic Graphs—0
METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer—0
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?Code0
Multilingual Lexical Simplification via Paraphrase GenerationCode0
Exploring Format Consistency for Instruction TuningCode0
Reconciling the accuracy-diversity trade-off in recommendations—0
Self-Supervised Visual Acoustic Matching—0
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