Toward a perspectivist turn in ground truthing for predictive computing

F Cabitza, A Campagner, V Basile - … of the AAAI Conference on Artificial …, 2023 - ojs.aaai.org
Abstract Most current Artificial Intelligence applications are based on supervised Machine
Learning (ML), which ultimately grounds on data annotated by small teams of experts or …

[PDF][PDF] Machine learning for stock market forecasting: a review of models and accuracy

DI Ajiga, RA Adeleye, TS Tubokirifuruar… - Finance & Accounting …, 2024 - researchgate.net
` MACHINE LEARNING FOR STOCK MARKET FORECASTING: A REVIEW OF MODELS AND
ACCURACY Page 1 Finance & Accounting Research Journal, Volume 6, Issue 2, February 2024 …

Enhancing Sample Utilization in Noise-Robust Deep Metric Learning With Subgroup-Based Positive-Pair Selection

Z Yu, Q Xu, Y Jiang, Y Sun… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The existence of noisy labels in real-world data negatively impacts the performance of deep
learning models. Although much research effort has been devoted to improving the …

Noise-resistant deep metric learning with probabilistic instance filtering

C Liu, H Yu, B Li, Z Shen, Z Gao, P Ren, X **e… - arxiv preprint arxiv …, 2021 - arxiv.org
Noisy labels are commonly found in real-world data, which cause performance degradation
of deep neural networks. Cleaning data manually is labour-intensive and time-consuming …

AI-empowered promotional video generation

C Liu - 2022 - dr.ntu.edu.sg
Promotional videos are rapidly becoming a popular form of product advertising on E-
commerce platforms. The traditional way of producing promotional videos is a time-, skill …