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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 7726–7750 of 9051 papers

TitleStatusHype
A Framework to Counteract Suboptimal User-Behaviors in Exploratory Learning Environments: an Application to MOOCs—0
STARS: Sensor-agnostic Transformer Architecture for Remote Sensing—0
Stars, Stripes, and Silicon: Unravelling the ChatGPT's All-American, Monochrome, Cis-centric Bias—0
2D Human Pose Estimation: New Benchmark and State of the Art Analysis—0
A Framework for Synthetic Audio Conversations Generation using Large Language Models—0
2-D Coherence Factor for Sidelobe and Ghost Suppressions in Radar Imaging—0
State-Space Models in Efficient Whispered and Multi-dialect Speech Recognition—0
A Framework for Ranking Content Providers Using Prompt Engineering and Self-Attention Network—0
Statistical Analysis of Received Signal Strength in Industrial IoT Distributed Massive MIMO Systems—0
Statistical Learning Theory Approach for Data Classification with l-diversity—0
Virtual Thin Slice: 3D Conditional GAN-based Super-resolution for CT Slice Interval—0
Unsourced Adversarial CAPTCHA: A Bi-Phase Adversarial CAPTCHA Framework—0
Statistical Results of Multivariate Fox-H Function for Exact Performance Analysis of RIS-Assisted Wireless Communication—0
Statistics of the Effective Massive MIMO Channel in Correlated Rician Fading—0
Statistics of the number of equilibria in random social dilemma evolutionary games with mutation—0
STC-IDS: Spatial-Temporal Correlation Feature Analyzing based Intrusion Detection System for Intelligent Connected Vehicles—0
Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generation—0
Steering Responsible AI: A Case for Algorithmic Pluralism—0
Steganalysis of Image with Adaptively Parametric Activation—0
Visible Light Optical Data Centre Links—0
Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning—0
AFP-CKSAAP: Prediction of Antifreeze Proteins Using Composition of k-Spaced Amino Acid Pairs with Deep Neural Network—0
GRAIL: A Benchmark for GRaph ActIve Learning in Dynamic Sensing Environments—0
Stigmergy-based collision-avoidance algorithm for self-organising swarms—0
ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning—0
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