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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 7701–7750 of 9051 papers

TitleStatusHype
Energy Clustering for Unsupervised Person Re-identification—0
Heterogeneous Collaborative Filtering—0
Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization—0
The economics of minority language use: theory and empirical evidence for a language game model—0
BooVAE: Boosting Approach for Continual Learning of VAECode0
Adaptively Sparse TransformersCode1
Earlier Isn't Always Better: Sub-aspect Analysis on Corpus and System Biases in SummarizationCode0
Latent Part-of-Speech Sequences for Neural Machine Translation—0
Virtual Thin Slice: 3D Conditional GAN-based Super-resolution for CT Slice Interval—0
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness—0
Evidence for a multi-level trophic organization of the human gut microbiomeCode0
Image Harmonization Dataset iHarmony4: HCOCO, HAdobe5k, HFlickr, and Hday2nightCode0
Improving End-to-End Sequential Recommendations with Intent-aware DiversificationCode0
The many faces of deep learning—0
DGSAN: Discrete Generative Self-Adversarial NetworkCode0
Power Efficient Discontinuous Reception in THz and mmWave Wireless Systems—0
Self-reinforcing Unsupervised Matching—0
Neural Text Summarization: A Critical Evaluation—0
Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning—0
The effects of ecological selection on species diversity and trait distribution: predictions and an empirical test—0
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks—0
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding DatasetsCode0
Dialog State Tracking with Reinforced Data Augmentation—0
Make a Face: Towards Arbitrary High Fidelity Face Manipulation—0
A Co-analysis Framework for Exploring Multivariate Scientific Data—0
Long and Diverse Text Generation with Planning-based Hierarchical Variational ModelCode0
SDIT: Scalable and Diverse Cross-domain Image TranslationCode0
Generating an Overview Report over Many Documents—0
Anomaly Detection in Video Sequence with Appearance-Motion CorrespondenceCode0
Imitation Learning for Sentence Generation with Dilated Convolutions Using Adversarial TrainingCode0
Deep learning on butterfly phenotypes tests evolution's oldest mathematical model—0
FlexNER: A Flexible LSTM-CNN Stack Framework for Named Entity Recognition—0
Towards Diverse and Accurate Image Captions via Reinforcing Determinantal Point ProcessCode0
A Multi-View Discriminant Learning Approach for Indoor Localization Using Bimodal Features of CSI—0
ConfigTron: Tackling network diversity with heterogeneous configurations—0
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric—0
Exploiting Cross-Lingual Speaker and Phonetic Diversity for Unsupervised Subword Modeling—0
Exploiting semi-supervised training through a dropout regularization in end-to-end speech recognition—0
Dynamic Scale Inference by Entropy Minimization—0
GridDehazeNet: Attention-Based Multi-Scale Network for Image DehazingCode0
Full-Stack Filters to Build Minimum Viable CNNsCode0
Multi-view Deep Subspace Clustering NetworksCode0
Symmetry-constrained Rectification Network for Scene Text Recognition—0
Graph based adaptive evolutionary algorithm for continuous optimization—0
Fully Automatic Video Colorization with Self-Regularization and DiversityCode0
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain ShiftCode0
ABD-Net: Attentive but Diverse Person Re-IdentificationCode0
PD-GAN: Adversarial Learning for Personalized Diversity-Promoting RecommendationCode0
Spatio-Temporal Prediction of Dialectal Variant Usage—0
The Romanian Corpus Annotated with Verbal Multiword Expressions—0
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