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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 1201–1250 of 9051 papers

TitleStatusHype
ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic SegmentationCode1
Bias Loss for Mobile Neural NetworksCode1
Conditional Sound Generation Using Neural Discrete Time-Frequency Representation LearningCode1
General Virtual Sketching Framework for Vector Line ArtCode1
Adaptable Agent Populations via a Generative Model of PoliciesCode1
COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive SensingCode1
Tailor: Generating and Perturbing Text with Semantic ControlsCode1
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiersCode1
eProduct: A Million-Scale Visual Search Benchmark to Address Product Recognition ChallengesCode1
Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain AdaptationCode1
Semi-Supervised Learning with Multi-Head Co-TrainingCode1
Diverse Video Generation using a Gaussian Process TriggerCode1
Wavelet Transform-assisted Adaptive Generative Modeling for ColorizationCode1
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis TransferCode1
Keiki: Towards Realistic Danmaku Generation via Sequential GANsCode1
Controllable Open-ended Question Generation with A New Question Type OntologyCode1
ResViT: Residual vision transformers for multi-modal medical image synthesisCode1
A Diverse Corpus for Evaluating and Developing English Math Word Problem SolversCode1
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros StudyCode1
O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance LearningCode1
RAILS: A Robust Adversarial Immune-inspired Learning SystemCode1
UMIC: An Unreferenced Metric for Image Captioning via Contrastive LearningCode1
Neural Fashion Image Captioning : Accounting for Data DiversityCode1
Repulsive Deep Ensembles are BayesianCode1
Domain-Smoothing Network for Zero-Shot Sketch-Based Image RetrievalCode1
Instance-Optimal Compressed Sensing via Posterior SamplingCode1
Calliar: An Online Handwritten Dataset for Arabic CalligraphyCode1
Heterogeneous Multi-task Learning with Expert DiversityCode1
LayoutTransformer: Scene Layout Generation With Conceptual and Spatial DiversityCode1
Simple GNN Regularisation for 3D Molecular Property Prediction & BeyondCode1
Learning to See by Looking at NoiseCode1
Unsupervised Behaviour Discovery with Quality-Diversity OptimisationCode1
Energy-Based Models for Code Generation under Compilability ConstraintsCode1
UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase PredictionCode1
Differentiable Quality DiversityCode1
Refiner: Refining Self-attention for Vision TransformersCode1
PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse DesignCode1
PreferenceNet: Encoding Human Preferences in Auction Design with Deep LearningCode1
Large-scale Unsupervised Semantic SegmentationCode1
Noise Conditional Flow Model for Learning the Super-Resolution SpaceCode1
Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task LearningCode1
Celebrating Diversity in Shared Multi-Agent Reinforcement LearningCode1
Barcode Method for Generative Model Evaluation driven by Topological Data AnalysisCode1
Generate, Prune, Select: A Pipeline for Counterspeech Generation against Online Hate SpeechCode1
RAD-TTS: Parallel Flow-Based TTS with Robust Alignment Learning and Diverse SynthesisCode1
SNIPS: Solving Noisy Inverse Problems StochasticallyCode1
Diversifying Dialog Generation via Adaptive Label SmoothingCode1
Towards Diverse Paragraph Captioning for Untrimmed VideosCode1
Transforming the Latent Space of StyleGAN for Real Face EditingCode1
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