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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 6551–6600 of 9051 papers

TitleStatusHype
Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing—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
MLGO: a Machine Learning Guided Compiler Optimizations FrameworkCode1
Fine-grained Semantic Constraint in Image Synthesis—0
Multi-Domain Image-to-Image Translation with Adaptive Inference Graph—0
FII-CenterNet: An Anchor-Free Detector With Foreground Attention for Traffic Object DetectionCode1
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
Scale-Aware Network with Regional and Semantic Attentions for Crowd Counting under Cluttered Background—0
VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios—0
Learning from Synthetic Shadows for Shadow Detection and RemovalCode1
Recommending Accurate and Diverse Items Using Bilateral Branch Network—0
Coreference Resolution: Are the eliminated spans totally worthless?—0
Exploring Inter-Channel Correlation for Diversity-Preserved Knowledge DistillationCode1
Cross-Modality Person Re-Identification via Modality Confusion and Center Aggregation—0
Diverse Image Style Transfer via Invertible Cross-Space Mapping—0
Out-of-Core Surface Reconstruction via Global TGV Minimization—0
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel LossCode1
Active Learning for Lane Detection: A Knowledge Distillation Approach—0
Channel Augmented Joint Learning for Visible-Infrared RecognitionCode0
StyleFormer: Real-Time Arbitrary Style Transfer via Parametric Style CompositionCode1
Partial Off-Policy Learning: Balance Accuracy and Diversity for Human-Oriented Image Captioning—0
DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense KnowledgeCode1
Faster and Smarter AutoAugment: Augmentation Policy Search Based on Dynamic Data-Clustering—0
Learning Disentangled Representations for Image Translation—0
BROS: A Pre-trained Language Model for Understanding Texts in Document—0
Preventing Value Function Collapse in Ensemble Q-Learning by Maximizing Representation Diversity—0
Robust Memory Augmentation by Constrained Latent Imagination—0
Towards Powerful Graph Neural Networks: Diversity Matters—0
Tradeoffs in Data Augmentation: An Empirical Study—0
NOSE Augment: Fast and Effective Data Augmentation Without Searching—0
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity—0
A Reduction Approach to Constrained Reinforcement Learning—0
Ensemble-based Adversarial Defense Using Diversified Distance Mapping—0
KETG: A Knowledge Enhanced Text Generation Framework—0
CIGMO: Learning categorical invariant deep generative models from grouped data—0
On Nondeterminism and Instability in Neural Network Optimization—0
Approximating Pareto Frontier through Bayesian-optimization-directed Robust Multi-objective Reinforcement Learning—0
Sample efficient Quality Diversity for neural continuous control—0
Deep Ensembles with Hierarchical Diversity PruningCode0
TaskSet: A Dataset of Optimization TasksCode0
Diversity Augmented Conditional Generative Adversarial Network for Enhanced Multimodal Image-to-Image TranslationCode0
Measuring GAN Training in Real Time—0
Learning a Non-Redundant Collection of Classifiers—0
Molecule Optimization by Explainable Evolution—0
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