arXiv Machine Learning By Wenzhuo Qian, Hailiang Zhao, Ziqi Wang, Zhipeng Gao, Jiayi Chen, Zhiwei Ling, Shuiguang Deng

ARMOR: A Robust Self-Supervised Framework for Root Cause Analysis in Microservices under Missing Modality

Read the original on arXiv Machine Learning →

arXiv:2603. 25538v3 Announce Type: replace Abstract: Automated incident management is critical for microservice reliability.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Aug 6

MoCA: Multi-modal Cross-masked Autoencoder for Digital Health Measurements

arXiv:2506. 02260v4 Announce Type: replace-cross Abstract: Wearable devices enable continuous multi-modal physiological and behavioral monitoring, yet analysis of these data streams faces fundamental challenges including the lack of gold-standard labels and incomplete sensor data.

By Howon Ryu, Yuliang Chen, Yacun Wang, Andrea Z. LaCroix, Chongzhi Di, Loki Natarajan, Yu Wang, Jingjing Zou
arXiv Machine Learning
Jun 16

Unsupervised Learning for Missing Modalities in Multimodal Learning

arXiv:2606. 15743v1 Announce Type: new Abstract: This paper addresses the missing-modality challenge in multi-modal learning by introducing Unsupervised Learning for Missing Modalities in Multi-Modal Learning (UL4M4), a flexible framework that imputes missing feature embeddings in a task-independent manner before supervised prediction.

By Hassan Ismkhan, Hamid Bouchahcia