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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 6376–6400 of 9051 papers

TitleStatusHype
Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model—0
Expanding, Retrieving and Infilling: Diversifying Cross-Domain Question Generation with Flexible TemplatesCode0
Making Use of Latent Space in Language GANs for Generating Diverse Text without Pre-training—0
From characters to words: the turning point of BPE mergesCode0
TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness—0
WakaVT: A Sequential Variational Transformer for Waka Generation—0
Towards Evaluating and Training Verifiably Robust Neural NetworksCode1
In&Out : Diverse Image Outpainting via GAN Inversion—0
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space ShrinkingCode1
Unconstrained Scene Generation with Locally Conditioned Radiance FieldsCode1
Rainbow Memory: Continual Learning with a Memory of Diverse SamplesCode1
Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite—0
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial TrainingCode0
Data Augmentation in a Hybrid Approach for Aspect-Based Sentiment AnalysisCode0
Self-supervised Discriminative Feature Learning for Deep Multi-view ClusteringCode1
Defect-GAN: High-Fidelity Defect Synthesis for Automated Defect Inspection—0
Deep Ensemble Collaborative Learning by using Knowledge-transfer Graph for Fine-grained Object Classification—0
Automated Backend-Aware Post-Training Quantization—0
A Genetic Algorithm approach to Asymmetrical Blotto Games with Heterogeneous Valuations—0
Continual Speaker Adaptation for Text-to-Speech Synthesis—0
Input-Output Balanced Framework for Long-tailed LiDAR Semantic Segmentation—0
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity MaximizationCode1
Disentanglement-based Cross-Domain Feature Augmentation for Effective Unsupervised Domain Adaptive Person Re-identification—0
Adversarial Imitation Learning with Trajectorial Augmentation and CorrectionCode0
Spatial-spectral Hyperspectral Image Classification via Multiple Random Anchor Graphs Ensemble Learning—0
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