2 papers
cs.LG2026
Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
Dang Nguyen, Paymon Haddad, Eric Gan +1
Can we modify the training data distribution to encourage the underlying optimization method toward finding solutions with superior generalization performance on in-distribution da…
cs.LG2025
IBMA: An Imputation-Based Mixup Augmentation Using Self-Supervised Learning for Time Series Data
Dang Nha Nguyen, Hai Dang Nguyen, Khoa Tho Anh Nguyen
Data augmentation in time series forecasting plays a crucial role in enhancing model performance by introducing variability while maintaining the underlying temporal patterns. Howe…