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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 7226–7250 of 9051 papers

TitleStatusHype
Safe Perception -- A Hierarchical Monitor Approach—0
Analysis of Evolutionary Behavior in Self-Learning Media Search Engines—0
Sails and Anchors: The Complementarity of Exploratory and Exploitative Scientists in Knowledge Creation—0
Zero-Shot Human-Object Interaction Synthesis with Multimodal Priors—0
Analysis and Modeling of Behavioral Changes in a News Service—0
SALE-Based Offline Reinforcement Learning with Ensemble Q-Networks—0
Saliency-Based diversity and fairness Metric and FaceKeepOriginalAugment: A Novel Approach for Enhancing Fairness and Diversity—0
Saliency Diversified Deep Ensemble for Robustness to Adversaries—0
Analysing of 3D MIMO Communication Beamforming in Linear and Planar Arrays—0
Salient Slices: Improved Neural Network Training and Performance with Image Entropy—0
Analysing Equilibrium States for Population Diversity—0
An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints—0
Sammaan@LT-EDI-ACL2022: Ensembled Transformers Against Homophobia and Transphobia—0
An Agent-based Simulation of the Effectiveness of Creative Leadership—0
An Agent-based Model of the Cognitive Mechanisms Underlying the Origins of Creative Cultural Evolution—0
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks—0
Sample efficient Quality Diversity for neural continuous control—0
Sample Efficient Robot Learning in Supervised Effect Prediction Tasks—0
Sample-Efficient Unsupervised Domain Adaptation of Speech Recognition Systems A case study for Modern Greek—0
SampleFix: Learning to Generate Functionally Diverse Fixes—0
SampleMix: A Sample-wise Pre-training Data Mixing Strategey by Coordinating Data Quality and Diversity—0
Sampling Approach Matters: Active Learning for Robotic Language Acquisition—0
Sampling from Probabilistic Submodular Models—0
Contextually Plausible and Diverse 3D Human Motion Prediction—0
Experiences from Creating a Benchmark for Sentiment Classification for Varieties of English—0
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