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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 7101–7150 of 9051 papers

TitleStatusHype
The Bures Metric for Generative Adversarial Networks—0
Personalized Federated Learning with Moreau EnvelopesCode1
A Note on the Global Convergence of Multilayer Neural Networks in the Mean Field Regime—0
Diversity Policy Gradient for Sample Efficient Quality-Diversity Optimization—0
Neural Ensemble Search for Uncertainty Estimation and Dataset ShiftCode1
Geodesic-HOF: 3D Reconstruction Without Cutting Corners—0
Non-local Policy Optimization via Diversity-regularized Collaborative Exploration—0
Language-Conditioned Goal Generation: a New Approach to Language Grounding in RL—0
Learning Diverse Representations for Fast Adaptation to Distribution Shift—0
Information Extraction of Clinical Trial Eligibility CriteriaCode1
Attribute analysis with synthetic dataset for person re-identification—0
Towards control of opinion diversity by introducing zealots into a polarised social groupCode0
Grounding Language to Autonomously-Acquired Skills via Goal GenerationCode1
Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL—0
Mental Workload and Language Production in Non-Native Speaker IPA Interaction—0
PeopleMap: Visualization Tool for Mapping Out Researchers using Natural Language ProcessingCode1
Fully Unsupervised Diversity Denoising with Convolutional Variational AutoencodersCode1
Hypergraph Clustering for Finding Diverse and Experienced GroupsCode0
HausaMT v1.0: Towards English-Hausa Neural Machine Translation—0
Self-Distillation as Instance-Specific Label SmoothingCode1
Ethical Considerations and Statistical Analysis of Industry Involvement in Machine Learning Research—0
EDCompress: Energy-Aware Model Compression for Dataflows—0
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and Experimental Study—0
Skill Discovery of Coordination in Multi-agent Reinforcement Learning—0
Optimally Combining Classifiers for Semi-Supervised LearningCode0
Connecting User and Item Perspectives in Popularity Debiasing for Collaborative Recommendation—0
An Interference-Free Filter-Bank Multicarrier System Applicable for MIMO Channels—0
MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal AnglesCode1
Enhancing Facial Data Diversity with Style-based Face Aging—0
Prague Dependency Treebank -- Consolidated 1.0—0
Using Stable Matching to Optimize the Balance between Accuracy and Diversity in Recommendation—0
The Importance of Open-Endedness (for the Sake of Open-Endedness)—0
An Improved LSHADE-RSP Algorithm with the Cauchy Perturbation: iLSHADE-RSP—0
Uncertainty quantification in medical image segmentation with normalizing flowsCode1
Cross-model Back-translated Distillation for Unsupervised Machine TranslationCode0
Nested Scale Editing for Conditional Image Synthesis—0
From Probability to Consilience: How Explanatory Values Implement Bayesian Reasoning—0
Transforming Multi-Concept Attention into Video Summarization—0
Distribution Aligned Multimodal and Multi-Domain Image Stylization—0
Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient ExplorationCode0
Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition—0
Exploiting Joint Robustness to Adversarial Perturbations—0
UCTGAN: Diverse Image Inpainting Based on Unsupervised Cross-Space Translation—0
Learning Unseen Concepts via Hierarchical Decomposition and Composition—0
Progressive Mirror Detection—0
Overcoming Multi-Model Forgetting in One-Shot NAS With Diversity MaximizationCode1
Fast Texture Synthesis via Pseudo OptimizerCode0
Bayesian Adversarial Human Motion SynthesisCode1
Nested Scale-Editing for Conditional Image Synthesis—0
TA-Student VQA: Multi-Agents Training by Self-Questioning—0
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