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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 3201–3225 of 9051 papers

TitleStatusHype
3D Neural Field Generation using Triplane Diffusion—0
Enhancing weed detection performance by means of GenAI-based image augmentation—0
Invariance Principle Meets Vicinal Risk Minimization—0
ENOVA: Autoscaling towards Cost-effective and Stable Serverless LLM Serving—0
Enriched Functional Tree-Based Classifiers: A Novel Approach Leveraging Derivatives and Geometric Features—0
StyLitGAN: Prompting StyleGAN to Produce New Illumination Conditions—0
Exploring structure diversity in atomic resolution microscopy with graph neural networks—0
Enrich the content of the image Using Context-Aware Copy Paste—0
Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models—0
Ensemble-based Adversarial Defense Using Diversified Distance Mapping—0
Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness—0
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision—0
Co-existence of Micro, Pico and Atto Cells in Optical Wireless Communication—0
Diversity-Achieving Slow-DropBlock Network for Person Re-Identification—0
Ensemble Feature Extraction for Multi-Container Quality-Diversity Algorithms—0
Ensemble Federated Adversarial Training with Non-IID data—0
DiversiTree: A New Method to Efficiently Compute Diverse Sets of Near-Optimal Solutions to Mixed-Integer Optimization Problems—0
Ensemble Forecasting of Monthly Electricity Demand using Pattern Similarity-based Methods—0
Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes—0
Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction—0
Ensemble Methodology:Innovations in Credit Default Prediction Using LightGBM, XGBoost, and LocalEnsemble—0
Ensemble of ACCDOA- and EINV2-based Systems with D3Nets and Impulse Response Simulation for Sound Event Localization and Detection—0
An investigation into language complexity of World-of-Warcraft game-external texts—0
A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels—0
Breaking the mold: The challenge of large scale MARL specialization—0
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