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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 8001–8050 of 9051 papers

TitleStatusHype
Enhancing the long-term performance of recommender system—0
Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data—0
Describing like humans: on diversity in image captioningCode0
Imbalanced Sentiment Classification Enhanced with Discourse Marker—0
FVD: A new Metric for Video Generation—0
Deep Co-Training for Semi-Supervised Image SegmentationCode0
Initial Crypto-asset Offerings (ICOs), tokenization and corporate governance—0
Genetic drift in range expansions is very sensitive to density feedback in dispersal and growth—0
Diversity with Cooperation: Ensemble Methods for Few-Shot ClassificationCode0
Generating Diverse High-Resolution Images with VQ-VAE—0
A Probabilistic Bitwise Genetic Algorithm for B-Spline based Image Deformation Estimation—0
Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder—0
Visible Light Optical Data Centre Links—0
Diversifying Reply Suggestions using a Matching-Conditional Variational Autoencoder—0
Deep Generative Inpainting with Comparative Sample Augmentation—0
2-D Coherence Factor for Sidelobe and Ghost Suppressions in Radar Imaging—0
RAP-Net: Recurrent Attention Pooling Networks for Dialogue Response Selection—0
Non-rigid 3D shape retrieval based on multi-view metric learning—0
Implementing a Concept Network Model—0
Data Augmentation for Leaf Segmentation and Counting Tasks in Rosette Plants—0
Distributed Maximization of Submodular plus Diversity Functions for Multi-label Feature Selection on Huge Datasets—0
Gradient based sample selection for online continual learningCode0
Im2Pencil: Controllable Pencil Illustration from PhotographsCode0
How to Make Swarms Open-Ended? Evolving Collective Intelligence Through a Constricted Exploration of Adjacent Possibles—0
Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation—0
Adaptive Genomic Evolution of Neural Network Topologies (AGENT) for State-to-Action Mapping in Autonomous Agents—0
Multi-agent query reformulation: Challenges and the role of diversity—0
MirrorGAN: Learning Text-to-image Generation by RedescriptionCode0
Superpixel-based Color Transfer—0
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural NetworksCode0
Mode Seeking Generative Adversarial Networks for Diverse Image SynthesisCode0
Individual-Level SNP Diversity and Similarity Profiles—0
Pluralistic Image CompletionCode0
Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering—0
GRATIS: GeneRAting TIme Series with diverse and controllable characteristicsCode0
Negative Training for Neural Dialogue Response GenerationCode0
Self-Supervised Learning of Face Representations for Video Face ClusteringCode0
Deep Generative Design: Integration of Topology Optimization and Generative Models—0
Jointly Optimizing Diversity and Relevance in Neural Response Generation—0
Unifying Ensemble Methods for Q-learning via Social Choice Theory—0
Multilingual Neural Machine Translation with Knowledge DistillationCode0
Ranking in Genealogy: Search Results Fusion at Ancestry—0
Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation—0
Improving Neural Response Diversity with Frequency-Aware Cross-Entropy LossCode0
Diversity of Ensembles for Data Stream Classification—0
On How Users Edit Computer-Generated Visual Stories—0
Operational Neural Networks—0
To Ensemble or Not Ensemble: When does End-To-End Training Fail?Code0
Guiding Neuroevolution with Structural Objectives—0
Neural Machine Translation for Cebuano to Tagalog with Subword Unit Translation—0
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