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

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Showing 7151–7175 of 9051 papers

TitleStatusHype
Local Implicit Grid Representations for 3D Scenes—0
Study on Patterns and Effect of Task Diversity in Software Crowdsourcing—0
CoDiNet: Path Distribution Modeling with Consistency and Diversity for Dynamic RoutingCode0
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing—0
Tracking, exploring and analyzing recent developments in German-language online press in the face of the coronavirus crisis: cOWIDplus Analysis and cOWIDplus Viewer—0
Reconfigurable Intelligent Surface-Aided Grant-Free Access for Uplink URLLC—0
Interlayer and Intralayer Scale Aggregation for Scale-invariant Crowd Counting—0
Generator and Critic: A Deep Reinforcement Learning Approach for Slate Re-ranking in E-commerce—0
Discriminative Active Learning for Domain Adaptation—0
Feature Statistics Guided Efficient Filter Pruning—0
ASAPP-ASR: Multistream CNN and Self-Attentive SRU for SOTA Speech Recognition—0
Novel Policy Seeking with Constrained OptimizationCode0
Reducing Overlearning through Disentangled Representations by Suppressing Unknown TasksCode0
Batch Decorrelation for Active Metric LearningCode0
Greedy Algorithm almost Dominates in Smoothed Contextual Bandits—0
A Diverse Clustering Particle Swarm Optimizer for Dynamic Environment: To Locate and Track Multiple Optima—0
Controllable Multi-Interest Framework for RecommendationCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
Spatial Information Considered Network for Scene ClassificationCode0
The NTNU System at the Interspeech 2020 Non-Native Children's Speech ASR Challenge—0
Multi-View Collaborative Network EmbeddingCode1
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks—0
Decision Fusion in Space-Time Spreading aided Distributed MIMO WSNs—0
Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search—0
Investigating Bias in Deep Face Analysis: The KANFace Dataset and Empirical Study—0
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