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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 4876–4900 of 9051 papers

TitleStatusHype
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training—0
Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and AccuracyCode0
DMDD: A Large-Scale Dataset for Dataset Mentions Detection—0
Language-Universal Phonetic Representation in Multilingual Speech Pretraining for Low-Resource Speech Recognition—0
Few-shot 3D Shape Generation—0
Evolutionary Diversity Optimisation in Constructing Satisfying Assignments—0
Improving Multimodal Joint Variational Autoencoders through Normalizing Flows and Correlation Analysis—0
Remembering What Is Important: A Factorised Multi-Head Retrieval and Auxiliary Memory Stabilisation Scheme for Human Motion Prediction—0
Use of Speech Impairment Severity for Dysarthric Speech Recognition—0
Improving Recommendation System Serendipity Through Lexicase Selection—0
Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning—0
Augmented Message Passing Stein Variational Gradient Descent—0
Confidence-Guided Semi-supervised Learning in Land Cover Classification—0
Bridging the Gap: Enhancing the Utility of Synthetic Data via Post-Processing Techniques—0
Dynamics of niche construction in adaptable populations evolving in diverse environmentsCode0
Comparison of classifiers in challenge scheme—0
Fairness and Diversity in Information Access Systems—0
DarkBERT: A Language Model for the Dark Side of the Internet—0
Deep Reinforcement Learning-based Exploration of Web ApplicationsCode0
Private Training Set Inspection in MLaaS—0
OOD-Speech: A Large Bengali Speech Recognition Dataset for Out-of-Distribution Benchmarking—0
The Structure and Dynamics of Knowledge Graphs, with SuperficialityCode0
Deep Learning for Asynchronous Massive Access with Data Frame Length Diversity—0
Comparison of machine learning models applied on anonymized data with different techniques—0
Zero-shot racially balanced dataset generation using an existing biased StyleGAN2Code0
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