SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8201–8225 of 9051 papers

TitleStatusHype
Context-Dependent Diffusion Network for Visual Relationship Detection—0
Using Image Fairness Representations in Diversity-Based Re-ranking for Recommendations—0
Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerceCode0
Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question AnsweringCode0
Information-Theoretic Active Learning for Content-Based Image RetrievalCode0
Diversity and Sparsity: A New Perspective on Index Tracking—0
Structural Consistency and Controllability for Diverse Colorization—0
Why are Sequence-to-Sequence Models So Dull? Understanding the Low-Diversity Problem of Chatbots—0
BOLD5000: A public fMRI dataset of 5000 imagesCode0
Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification—0
Diverse and Coherent Paragraph Generation from Images—0
A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension—0
Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization—0
Stacking ensemble with parsimonious base models to improve generalization capability in the characterization of steel bolted components—0
Find and Focus: Retrieve and Localize Video Events with Natural Language Queries—0
Incremental Multi-graph Matching via Diversity and Randomness based Graph Clustering—0
Real-Time Hair Rendering using Sequential Adversarial Networks—0
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks—0
LUDB: a new open-access validation tool for electrocardiogram delineation algorithmsCode0
Gaussian Mixture Generative Adversarial Networks for Diverse Datasets, and the Unsupervised Clustering of Images—0
Matrix Factorization Equals Efficient Co-occurrence Representation—0
Diversity-Driven Selection of Exploration Strategies in Multi-Armed Bandits—0
Keyphrase Generation with Correlation Constraints—0
An Axiomatic Analysis of Diversity Evaluation Metrics: Introducing the Rank-Biased Utility MetricCode0
Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific VotersCode0
Show:102550
← PrevPage 329 of 363Next →

No leaderboard results yet.