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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 6626–6650 of 9051 papers

TitleStatusHype
Universal and generalizable restoration strategies for degraded ecological networks—0
Predictive Analysis for Optimizing Port Operations—0
Predictive modeling and anomaly detection in large-scale web portals through the CAWAL framework—0
Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning—0
Towards Open-Set Myoelectric Gesture Recognition via Dual-Perspective Inconsistency Learning—0
Preference-Conditioned Gradient Variations for Multi-Objective Quality-Diversity—0
Preference-Guided Diffusion for Multi-Objective Offline Optimization—0
An upper bound of the mutation probability in the genetic algorithm for general 0-1 knapsack problem—0
An Unsupervised Semantic Sentence Ranking Scheme for Text Documents—0
Preference Optimization with Multi-Sample Comparisons—0
Prefix-diffusion: A Lightweight Diffusion Model for Diverse Image Captioning—0
An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio—0
Pre-Optimized Irregular Arrays versus Moveable Antennas in Multi-User MIMO Systems—0
Preparing for Black Swans: The Antifragility Imperative for Machine Learning—0
Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms—0
Universal Cold RNA Phase Transitions—0
Universal Dependencies for Punjabi—0
Universal Features Guided Zero-Shot Category-Level Object Pose Estimation—0
Preserving Product Fidelity in Large Scale Image Recontextualization with Diffusion Models—0
Presto! Distilling Steps and Layers for Accelerating Music Generation—0
Universal Information Extraction as Unified Semantic Matching—0
Deep Single Image Deraining using An Asymetric Cycle Generative and Adversarial Framework—0
Pre-Training BERT on Arabic Tweets: Practical Considerations—0
An Unscented Kalman Filter-Informed Neural Network for Vehicle Sideslip Angle Estimation—0
Preventing Value Function Collapse in Ensemble Q-Learning by Maximizing Representation Diversity—0
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