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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 4701–4725 of 9051 papers

TitleStatusHype
Active Learning for Point Cloud Semantic Segmentation via Spatial-Structural Diversity Reasoning—0
Interactive Image Selection and Training for Brain Tumor Segmentation Network—0
Interactive Mars Image Content-Based Search with Interpretable Machine Learning—0
Towards a computational model of grammaticalization and lexical diversity—0
Interactive Speech and Noise Modeling for Speech Enhancement—0
Active Learning for Object Detection with Non-Redundant Informative Sampling—0
Interference-Limited Ultra-Reliable and Low-Latency Communications: Graph Neural Networks or Stochastic Geometry?—0
InterHandGen: Two-Hand Interaction Generation via Cascaded Reverse Diffusion—0
Interlayer and Intralayer Scale Aggregation for Scale-invariant Crowd Counting—0
Intermittent migration can induce pulses of speciation in a two-island system—0
Internal Feedback in Biological Control: Architectures and Examples—0
Beyond Spatial Pyramid Matching: Space-time Extended Descriptor for Action Recognition—0
Interpretable Classification from Skin Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study—0
Interpretable Directed Diversity: Leveraging Model Explanations for Iterative Crowd Ideation—0
Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition—0
Interpretable Diversity Analysis: Visualizing Feature Representations In Low-Cost Ensembles—0
Interpretable Learning Dynamics in Unsupervised Reinforcement Learning—0
Learning Coherent Matrixized Representation in Latent Space for Volumetric 4D Generation—0
Interpretable Visual Question Answering Referring to Outside Knowledge—0
Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation—0
Beyond Size and Class Balance: Alpha as a New Dataset Quality Metric for Deep Learning—0
Interspeech 2025 URGENT Speech Enhancement Challenge—0
Beyond Single-Point Judgment: Distribution Alignment for LLM-as-a-Judge—0
In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations—0
Intra-Ensemble in Neural Networks—0
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