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cs.LG2024
Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning
Jiaming Liu, Hongyuan Liu, Zhili Qin +4
The dynamic nature of open-world scenarios has attracted more attention to class incremental learning (CIL). However, existing CIL methods typically presume the availability of com…
cs.LG2024
Variational Deep Survival Machines: Survival Regression with Censored Outcomes
Qinxin Wang, Jiayuan Huang, Junhui Li +1
Survival regression aims to predict the time when an event of interest will take place, typically a death or a failure. A fully parametric method [18] is proposed to estimate the s…