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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 5201–5250 of 9051 papers

TitleStatusHype
Self-Segregating and Coordinated-Segregating Transformer for Focused Deep Multi-Modular Network for Visual Question Answering—0
Self-Supervised Deep Learning to Enhance Breast Cancer Detection on Screening Mammography—0
Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks—0
Self-supervised Human Mesh Recovery with Cross-Representation Alignment—0
Self-supervised Image Clustering from Multiple Incomplete Views via Constrastive Complementary Generation—0
Self-Supervised Light Field Depth Estimation Using Epipolar Plane Images—0
Self-supervised Multi-level Face Model Learning for Monocular Reconstruction at over 250 Hz—0
Self-supervised Representation Learning for Trip Recommendation—0
Self-Supervised Visual Acoustic Matching—0
Tunable Hybrid Proposal Networks for the Open World—0
Progressive Ensemble Networks for Zero-Shot Recognition—0
Self-Training for End-to-End Speech Recognition—0
Seller-side Outcome Fairness in Online Marketplaces—0
Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning—0
Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts—0
Semantic-Aware Representation of Multi-Modal Data for Data Ingress: A Literature Review—0
Semantic Cells: Evolutional Process to Acquire Sense Diversity of Items—0
Semantic Diversity by Phonetics for Accurate and Robust Machine Translation—0
Semantic Diversity for Natural Language Understanding Evaluation in Dialog Systems—0
Semantic Diversity in Dialogue with Natural Language Inference—0
Semantic-diversity transfer network for generalized zero-shot learning via inner disagreement based OOD detector—0
Semantic Diversity versus Visual Diversity in Visual Dictionaries—0
Semantic Example Guided Image-to-Image Translation—0
Semantic Exploration with Adaptive Gating for Efficient Problem Solving with Language Models—0
Semantic-Guided Generative Image Augmentation Method with Diffusion Models for Image Classification—0
Semantic Map Guided Synthesis of Wireless Capsule Endoscopy Images using Diffusion Models—0
Semantic Neighborhood Ordering in Multi-objective Genetic Programming based on Decomposition—0
Semantic-Rearrangement-Based Multi-Level Alignment for Domain Generalized Segmentation—0
Semantic Scene Completion with Multi-Feature Data Balancing Network—0
Semantics Disentangling for Text-to-Image Generation—0
Semantic Segmentation for Point Cloud Scenes via Dilated Graph Feature Aggregation and Pyramid Decoders—0
Semantics in Multi-objective Genetic Programming—0
Semantic uncertainty guides the extension of conventions to new referents—0
Semantic WordRank: Generating Finer Single-Document Summarizations—0
SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding—0
Semi-Implicit Generative Model—0
Semi-Instruct: Bridging Natural-Instruct and Self-Instruct for Code Large Language Models—0
Semi-Supervised Convolutional Neural Networks for Human Activity Recognition—0
Semi-supervised FusedGAN for Conditional Image Generation—0
Semi-Supervised Health Index Monitoring with Feature Generation and Fusion—0
Semi-Supervised Phone Classification using Deep Neural Networks and Stochastic Graph-Based Entropic Regularization—0
Sentence embedding with contrastive multi-views learning—0
Sentiment Classification in Swahili Language Using Multilingual BERT—0
SentiRec: Sentiment Diversity-aware Neural News Recommendation—0
Sequence to Sequence Mixture Model for Diverse Machine Translation—0
Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity—0
Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control—0
Sequencing Silicates in the IRS Debris Disk Catalog I: Methodology for Unsupervised Clustering—0
Sequential Condition Evolved Interaction Knowledge Graph for Traditional Chinese Medicine Recommendation—0
Sequential Deformation for Accurate Scene Text Detection—0
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