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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 2101–2125 of 9051 papers

TitleStatusHype
A Simple Dual-decoder Model for Generating Response with Sentiment—0
Computational Eco-Systems for Handwritten Digits Recognition—0
MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder—0
Diffusion Least Mean Square: Simulations—0
Diffusion-like recommendation with enhanced similarity of objects—0
Digital Twin-Oriented Complex Networked Systems based on Heterogeneous Node Features and Interaction Rules—0
Compression using Discrete Multi-Level Divisor Transform for Heterogeneous Sensor Data—0
Compress Guidance in Conditional Diffusion Sampling—0
A Simple Cooperative Diversity Method Based on Deep-Learning-Aided Relay Selection—0
Compressed Sensing with Approximate Priors via Conditional Resampling—0
A Simple Background Augmentation Method for Object Detection with Diffusion Model—0
AgroXAI: Explainable AI-Driven Crop Recommendation System for Agriculture 4.0—0
A Sentiment-Controllable Topic-to-Essay Generator with Topic Knowledge Graph—0
Comprehensive Video Understanding: Video summarization with content-based video recommender design—0
Diffusion-based Target Sampler for Unsupervised Domain Adaptation—0
Comprehensive Pathological Image Segmentation via Teacher Aggregation for Tumor Microenvironment Analysis—0
Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems—0
Comprehensive Annotation of Multiword Expressions in a Social Web Corpus—0
Compositional Zero-Shot Learning via Fine-Grained Dense Feature Composition—0
Active Inference and Human--Computer Interaction—0
Suppressing Model Overfitting for Image Super-Resolution Networks—0
Compositional Operators in Distributional Semantics—0
Compositional Fine-Grained Low-Shot Learning—0
A Semantically Consistent and Syntactically Variational Encoder-Decoder Framework for Paraphrase Generation—0
A Self-Commissioning Edge Computing Method for Data-Driven Anomaly Detection in Power Electronic Systems—0
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