ADAPT-MS achieves 0.66 RMSE unsupervised and 0.60 with 1000 labels on cross-platform MOOC satisfaction prediction by aligning representations and correcting platform biases.
A survey on transfer learning,
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Gen-ROTDA fits a target anchor with small labeled data, transfers residuals via robust OT with a generative feature generator and trims high-cost matches, achieving lowest MAE on 2025-2026 Citi Bike prediction and better stability than non-robust OT methods.
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Cross-Platform Domain Adaptation for Multi-Modal MOOC Learner Satisfaction Prediction
ADAPT-MS achieves 0.66 RMSE unsupervised and 0.60 with 1000 labels on cross-platform MOOC satisfaction prediction by aligning representations and correcting platform biases.
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Robust OT-Guided Generative Residual Domain Adaptation for Bike-Sharing Demand Prediction under Temporal Domain Shift
Gen-ROTDA fits a target anchor with small labeled data, transfers residuals via robust OT with a generative feature generator and trims high-cost matches, achieving lowest MAE on 2025-2026 Citi Bike prediction and better stability than non-robust OT methods.