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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 1701–1750 of 9051 papers

TitleStatusHype
Algorithmic Hiring and Diversity: Reducing Human-Algorithm Similarity for Better Outcomes—0
AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control—0
Data Distributional Properties As Inductive Bias for Systematic Generalization—0
Algorithmically probable mutations reproduce aspects of evolution such as convergence rate, genetic memory, and modularity—0
Data-dependent Gaussian Prior Objective for Language Generation—0
Attribute analysis with synthetic dataset for person re-identification—0
A Learning Scheme for Microgrid Islanding and Reconnection—0
Data Dieting in GAN Training—0
Data Diversity Matters for Robust Instruction Tuning—0
Data-Aware Device Scheduling for Federated Edge Learning—0
A Learning-Exploring Method to Generate Diverse Paraphrases with Multi-Objective Deep Reinforcement Learning—0
Data center top of rack switch to multiple spine switches optical wireless uplinks—0
Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessment—0
Attentive Aspect Modeling for Review-aware Recommendation—0
Evaluations at Work: Measuring the Capabilities of GenAI in Use—0
Data-Centric Long-Tailed Image Recognition—0
Attention in Diffusion Model: A Survey—0
Attention-Enhanced U-Net for Accurate Segmentation of COVID-19 Infected Lung Regions in CT Scans—0
AdaDNNs: Adaptive Ensemble of Deep Neural Networks for Scene Text Recognition—0
Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning—0
Attention-based Ensemble for Deep Metric Learning—0
Academic Case Reports Lack Diversity: Assessing the Presence and Diversity of Sociodemographic and Behavioral Factors related to Post COVID-19 Condition—0
Data Collection and Labeling Techniques for Machine Learning—0
Data-driven Discovery of Biophysical T Cell Receptor Co-specificity Rules—0
Attempt Towards Stress Transfer in Speech-to-Speech Machine Translation—0
AdaAugment: A Tuning-Free and Adaptive Approach to Enhance Data Augmentation—0
Abstractive and mixed summarization for long-single documents—0
Attacking Transformers with Feature Diversity Adversarial Perturbation—0
A trust-based recommendation method using network diffusion processes—0
Ada-adapter:Fast Few-shot Style Personlization of Diffusion Model with Pre-trained Image Encoder—0
A tool for computing diversity and consideration on differences between diversity indices—0
Atom Responding Machine for Dialog Generation—0
Data Augmentation in Earth Observation: A Diffusion Model Approach—0
Dynamic Latent Separation for Deep Learning—0
ATM-R: An Adaptive Tradeoff Model with Reference Points for Constrained Multiobjective Evolutionary Optimization—0
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization—0
A Time Series Analysis-Based Forecasting Framework for the Indian Healthcare Sector—0
Achieving Tight O(4^k) Runtime Bounds on Jump_k by Proving that Genetic Algorithms Evolve Near-Maximal Population Diversity—0
Activitynet 2019 Task 3: Exploring Contexts for Dense Captioning Events in Videos—0
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks—0
A Large Language Model for Feasible and Diverse Population Synthesis—0
α-TCVAE: On the relationship between Disentanglement and Diversity—0
A Taxonomy of Adaptive Traffic Signal Control—0
A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment—0
Data Augmentation for Seizure Prediction with Generative Diffusion Model—0
Data Augmentation with Adversarial Training for Cross-Lingual NLI—0
Data-Driven Discovery of Functional Cell Types that Improve Models of Neural Activity—0
A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling—0
A Systematic Survey on Deep Generative Models for Graph Generation—0
A K-means-based Multi-subpopulation Particle Swarm Optimization for Neural Network Ensemble—0
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