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cs.LG2026
Machine Learning under Imperfect Data: Challenges and Methods
Masoumeh Zareapoor
Machine-learning models are commonly developed under an assumption that training and test data are sufficiently complete, balanced, labelled, and drawn from compatible distribution…
cs.LG2026
Task Switching Without Forgetting via Proximal Decoupling
Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger +2
In continual learning, the primary challenge is to learn new information without forgetting old knowledge. A common solution addresses this trade-off through regularization, penali…
cs.LG2026
Finding Structure in Continual Learning
Pourya Shamsolmoali, Masoumeh Zareapoor
Learning from a stream of tasks usually pits plasticity against stability: acquiring new knowledge often causes catastrophic forgetting of past information. Most methods address th…