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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 5051–5100 of 9051 papers

TitleStatusHype
Redrawing attendance boundaries to promote racial and ethnic diversity in elementary schools—0
Siamese Graph Learning for Semi-supervised Age EstimationCode0
ODIN: On-demand Data Formulation to Mitigate Dataset Lock-in—0
Nearest-Neighbor Inter-Intra Contrastive Learning from Unlabeled Videos—0
Architext: Language-Driven Generative Architecture Design—0
Compressed Heterogeneous Graph for Abstractive Multi-Document SummarizationCode0
One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic NetworksCode0
AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Image—0
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning—0
Unifying Layout Generation with a Decoupled Diffusion Model—0
Knowledge-augmented Few-shot Visual Relation Detection—0
An Unscented Kalman Filter-Informed Neural Network for Vehicle Sideslip Angle Estimation—0
The evolution of cooperation and diversity by integrated indirect reciprocity—0
Interpretable Visual Question Answering Referring to Outside Knowledge—0
Deep Occupancy-Predictive Representations for Autonomous Driving—0
Bias, diversity, and challenges to fairness in classification and automated text analysis. From libraries to AI and back—0
Lformer: Text-to-Image Generation with L-shape Block Parallel Decoding—0
Controlled Diversity with Preference : Towards Learning a Diverse Set of Desired SkillsCode0
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer LearningCode0
Emergent competition shapes the ecological properties of multi-trophic ecosystems—0
Mining both Commonality and Specificity from Multiple Documents for Multi-Document Summarization—0
Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output CodesCode0
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing SymmetriesCode0
Data Augmentation for Generating Synthetic Electrogastrogram Time SeriesCode0
Effective Visualization and Analysis of Recommender Systems—0
pyribs: A Bare-Bones Python Library for Quality Diversity Optimization—0
Toward Robust Uncertainty Estimation with Random Activation FunctionsCode0
DEff-GAN: Diverse Attribute Transfer for Few-Shot Image SynthesisCode0
Can We Use Diffusion Probabilistic Models for 3D Motion Prediction?—0
Finding Support Examples for In-Context Learning—0
Cross-modal Face- and Voice-style Transfer—0
Diversity matters: Robustness of bias measurements in WikidataCode0
Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets—0
Speech Corpora Divergence Based Unsupervised Data Selection for ASR—0
Closed-loop Error Correction Learning Accelerates Experimental Discovery of Thermoelectric MaterialsCode0
Spatial-temporal Transformer-guided Diffusion based Data Augmentation for Efficient Skeleton-based Action Recognition—0
Medical visual question answering using joint self-supervised learning—0
Tractable Diversity: Scalable Multiperspective Ontology Management via Standpoint EL—0
Vagueness in Predicates and Objects—0
Lasting Diversity and Superior Runtime Guarantees for the (μ+1) Genetic Algorithm—0
Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding ExplorationCode0
In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across LanguagesCode0
Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model MarketCode0
Deep Active Learning in the Presence of Label Noise: A Survey—0
Learning from Multiple Sources for Data-to-Text and Text-to-DataCode0
Commonality in Recommender Systems: Evaluating Recommender Systems to Enhance Cultural Citizenship—0
Cyclic Delay-Doppler Shift: A Simple Transmit Diversity Technique for Delay-Doppler Waveforms in Doubly Selective Channels—0
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles—0
Feasible Recourse Plan via Diverse InterpolationCode0
Texturize a GAN Using a Single Image—0
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