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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 3851–3875 of 9051 papers

TitleStatusHype
Distributed Deep Learning for Modulation Classification in 6G Cell-Free Wireless Networks—0
Historical Astronomical Diagrams Decomposition in Geometric Primitives—0
Humans-in-the-Building: Getting Rid of Thermostats for Optimal Thermal Comfort Control in Energy Management Systems—0
Prompt Selection and Augmentation for Few Examples Code Generation in Large Language Model and its Application in Robotics Control—0
Complementing cell taxonomies with a multicellular functional analysis of tissues—0
Process-Aware Analysis of Treatment Paths in Heart Failure Patients: A Case Study—0
Multi-Scale Implicit Transformer with Re-parameterize for Arbitrary-Scale Super-Resolution—0
Multiple Population Alternate Evolution Neural Architecture Search—0
Attacking Transformers with Feature Diversity Adversarial Perturbation—0
BSDA: Bayesian Random Semantic Data Augmentation for Medical Image ClassificationCode0
Speeding up 6-DoF Grasp Sampling with Quality-Diversity—0
Can Generative Models Improve Self-Supervised Representation Learning?Code0
Augmentations vs Algorithms: What Works in Self-Supervised Learning—0
CLIP-Gaze: Towards General Gaze Estimation via Visual-Linguistic Model—0
Aligning GPTRec with Beyond-Accuracy Goals with Reinforcement LearningCode0
Attempt Towards Stress Transfer in Speech-to-Speech Machine Translation—0
On-demand Quantization for Green Federated Generative Diffusion in Mobile Edge Networks—0
Greater than the sum of its parts: The role of minority and majority status in collaborative problem-solving communication—0
A New Benchmark for Evaluating Automatic Speech Recognition in the Arabic Call Domain—0
Beyond Major Product Prediction: Reproducing Reaction Mechanisms with Machine Learning Models Trained on a Large-Scale Mechanistic Dataset—0
Cultural-Aware AI Model for Emotion RecognitionCode0
Kernel Correlation-Dissimilarity for Multiple Kernel k-Means Clustering—0
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN—0
Illuminating the property space in crystal structure prediction using Quality-Diversity algorithms—0
Bridging Diversity and Uncertainty in Active learning with Self-Supervised Pre-Training—0
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