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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 1251–1300 of 9051 papers

TitleStatusHype
Transforming the Latent Space of StyleGAN for Real Face EditingCode1
ResT: An Efficient Transformer for Visual RecognitionCode1
The Herbarium 2021 Half-Earth Challenge DatasetCode1
ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learningCode1
Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption ModelsCode1
Bilingual Mutual Information Based Adaptive Training for Neural Machine TranslationCode1
One2Set: Generating Diverse Keyphrases as a SetCode1
Profiling Pareto Front With Multi-Objective Stein Variational Gradient DescentCode1
Improving Contrastive Learning on Imbalanced Data via Open-World SamplingCode1
An Empirical Study of Vehicle Re-Identification on the AI City ChallengeCode1
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
Plot and Rework: Modeling Storylines for Visual StorytellingCode1
Semantic Diversity Learning for Zero-Shot Multi-label ClassificationCode1
Learning to Generate Novel Scene Compositions from Single Images and VideosCode1
Improving Adversarial Transferability with Gradient RefiningCode1
Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input ModalitiesCode1
Stochastic Image-to-Video Synthesis using cINNsCode1
SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of ExpertsCode1
Meta-Learning-Based Deep Reinforcement Learning for Multiobjective Optimization ProblemsCode1
PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose EstimationCode1
PD-GAN: Probabilistic Diverse GAN for Image InpaintingCode1
The Tracking Machine Learning challenge : Throughput phaseCode1
Few-Shot Video Object DetectionCode1
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space EmbeddingCode1
LasHeR: A Large-scale High-diversity Benchmark for RGBT TrackingCode1
CompOFA: Compound Once-For-All Networks for Faster Multi-Platform DeploymentCode1
Practical Wide-Angle Portraits Correction with Deep Structured ModelsCode1
Vision Transformers with Patch DiversificationCode1
LGD-GCN: Local and Global Disentangled Graph Convolutional NetworksCode1
Towards Accurate Text-based Image Captioning with Content Diversity ExplorationCode1
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable SimulationCode1
Portfolio Search and Optimization for General Strategy Game-PlayingCode1
Diverse and Specific Clarification Question Generation with KeywordsCode1
SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal ConversationsCode1
Optimal Counterfactual Explanations for Scorecard modellingCode1
Ego-Exo: Transferring Visual Representations from Third-person to First-person VideosCode1
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative LearningCode1
Sentence-Permuted Paragraph GenerationCode1
Aligning Latent and Image Spaces to Connect the UnconnectableCode1
Sparse Attention with Linear UnitsCode1
Few-shot Image Generation via Cross-domain CorrespondenceCode1
Deep Time Series Forecasting with Shape and Temporal CriteriaCode1
Contrastive Syn-to-Real GeneralizationCode1
Extraction of instantaneous frequencies and amplitudes in nonstationary time-series dataCode1
Interpretable Unsupervised Diversity Denoising and Artefact RemovalCode1
Towards Evaluating and Training Verifiably Robust Neural NetworksCode1
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
Self-supervised Discriminative Feature Learning for Deep Multi-view ClusteringCode1
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