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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 1851–1875 of 9051 papers

TitleStatusHype
Genetic Algorithm-based Routing and Scheduling for Wildfire Suppression using a Team of UAVs—0
GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and DovesCode0
Utilizing TTS Synthesized Data for Efficient Development of Keyword Spotting Model—0
Constructing Enhanced Mutual Information for Online Class-Incremental Learning—0
The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European LanguagesCode0
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text GenerationCode1
Exploring the Role of Node Diversity in Directed Graph Representation LearningCode0
Ontology of Belief Diversity: A Community-Based Epistemological Approach—0
Network Inversion of Convolutional Neural Nets—0
Quantum-Inspired Evolutionary Algorithms for Feature Subset Selection: A Comprehensive Survey—0
PEFT-U: Parameter-Efficient Fine-Tuning for User PersonalizationCode0
Exploring the Effect of Dataset Diversity in Self-Supervised Learning for Surgical Computer VisionCode2
Enhancing Diversity in Multi-objective Feature Selection—0
XS-VID: An Extremely Small Video Object Detection Dataset—0
The FIGNEWS Shared Task on News Media Narratives—0
Self-Supervision Improves Diffusion Models for Tabular Data ImputationCode1
Multipath Identification and Mitigation with FDA-MIMO Radar—0
Image Segmentation via Divisive Normalization: dealing with environmental diversity—0
Diversity in Choice as Majorization—0
Pose Estimation from Camera Images for Underwater Inspection—0
Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial OptimizationCode1
A Quantum Leaky Integrate-and-Fire Spiking Neuron and NetworkCode1
Can time series forecasting be automated? A benchmark and analysis—0
Synth4Kws: Synthesized Speech for User Defined Keyword Spotting in Low Resource Environments—0
Topology Reorganized Graph Contrastive Learning with Mitigating Semantic Drift—0
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