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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 4301–4325 of 9051 papers

TitleStatusHype
Spatial-temporal Transformer-guided Diffusion based Data Augmentation for Efficient Skeleton-based Action Recognition—0
Medical visual question answering using joint self-supervised learning—0
Vagueness in Predicates and Objects—0
Tractable Diversity: Scalable Multiperspective Ontology Management via Standpoint EL—0
Lasting Diversity and Superior Runtime Guarantees for the (μ+1) Genetic Algorithm—0
Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding ExplorationCode0
In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across LanguagesCode0
Diverse Policy Optimization for Structured Action SpaceCode1
Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model MarketCode0
Cyclic Delay-Doppler Shift: A Simple Transmit Diversity Technique for Delay-Doppler Waveforms in Doubly Selective Channels—0
Feasible Recourse Plan via Diverse InterpolationCode0
Learning from Multiple Sources for Data-to-Text and Text-to-DataCode0
Commonality in Recommender Systems: Evaluating Recommender Systems to Enhance Cultural Citizenship—0
Deep Active Learning in the Presence of Label Noise: A Survey—0
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles—0
Texturize a GAN Using a Single Image—0
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management—0
Learning temporal relationships between symbols with Laplace Neural Manifolds—0
Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno Effect—0
Metropolis Theorem and Its Applications in Single Image Detail EnhancementCode0
One-Pot Multi-Frame Denoising—0
Towards Radar Emitter Recognition in Changing Environments with Domain Generalization—0
OTFS Signaling for SCMA With Coordinated Multi-Point Vehicle Communications—0
AfriSenti: A Twitter Sentiment Analysis Benchmark for African LanguagesCode1
Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord Questions—0
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