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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 6801–6850 of 9051 papers

TitleStatusHype
STAR-RISs: Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surfaces—0
Automatic Preference Based Multi-objective Evolutionary Algorithm on Vehicle Fleet Maintenance Scheduling Optimization—0
A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations—0
Investors Embrace Gender Diversity, Not Female CEOs: The Role of Gender in Startup Fundraising—0
Challenges Encountered in Turkish Natural Language Processing Studies—0
Neural-based Modeling for Performance Tuning of Spark Data AnalyticsCode0
Macroscopic Control of Text Generation for Image Captioning—0
Deep Epidemiological Modeling by Black-box Knowledge Distillation: An Accurate Deep Learning Model for COVID-19—0
Clustering Future Scenarios Based on Predicted Range Maps—0
Illuminating the Space of Beatable Lode Runner Levels Produced By Various Generative Adversarial NetworksCode0
Is the Capability approach a useful tool for decision aiding in public policy making?—0
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving—0
SceneGen: Learning to Generate Realistic Traffic Scenes—0
DivSwapper: Towards Diversified Patch-based Arbitrary Style Transfer—0
Binary strings of finite VC dimension—0
Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing—0
Operationalizing Framing to Support Multiperspective Recommendations of Opinion Pieces—0
Probabilistic Inference for Learning from Untrusted Sources—0
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation—0
Network Slicing for eMBB and mMTC with NOMA and Space Diversity Reception—0
Fine-grained Semantic Constraint in Image Synthesis—0
Multi-Domain Image-to-Image Translation with Adaptive Inference Graph—0
Manifold Interpolation for Large-Scale Multi-Objective Optimization via Generative Adversarial Networks—0
Analyzing the Stability of Non-coplanar Circumbinary Planets using Machine Learning—0
Object Detection for Understanding Assembly Instruction Using Context-aware Data Augmentation and Cascade Mask R-CNN—0
Learning Guided Electron Microscopy with Active AcquisitionCode0
Deep Reinforcement Learning with Quantum-inspired Experience Replay—0
VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios—0
Scale-Aware Network with Regional and Semantic Attentions for Crowd Counting under Cluttered Background—0
Coreference Resolution: Are the eliminated spans totally worthless?—0
Recommending Accurate and Diverse Items Using Bilateral Branch Network—0
Ensemble-based Adversarial Defense Using Diversified Distance Mapping—0
KETG: A Knowledge Enhanced Text Generation Framework—0
A Reduction Approach to Constrained Reinforcement Learning—0
Approximating Pareto Frontier through Bayesian-optimization-directed Robust Multi-objective Reinforcement Learning—0
Rethinking Parameter Counting: Effective Dimensionality Revisited—0
Diversity Augmented Conditional Generative Adversarial Network for Enhanced Multimodal Image-to-Image TranslationCode0
BROS: A Pre-trained Language Model for Understanding Texts in Document—0
Towards Powerful Graph Neural Networks: Diversity Matters—0
Active Learning for Lane Detection: A Knowledge Distillation Approach—0
Channel Augmented Joint Learning for Visible-Infrared RecognitionCode0
Learning to Generate Videos Using Neural Uncertainty Priors—0
Partial Off-Policy Learning: Balance Accuracy and Diversity for Human-Oriented Image Captioning—0
On Nondeterminism and Instability in Neural Network Optimization—0
Out-of-Core Surface Reconstruction via Global TGV Minimization—0
Cross-Modality Person Re-Identification via Modality Confusion and Center Aggregation—0
Robust Memory Augmentation by Constrained Latent Imagination—0
Faster and Smarter AutoAugment: Augmentation Policy Search Based on Dynamic Data-Clustering—0
ON NEURAL NETWORK GENERALIZATION VIA PROMOTING WITHIN-LAYER ACTIVATION DIVERSITY—0
Preventing Value Function Collapse in Ensemble Q-Learning by Maximizing Representation Diversity—0
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