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Federated mutual learning: a collaborative machine learning method for heterogeneous data, models, and objectives., , , , , , , and . Frontiers Inf. Technol. Electron. Eng., 24 (10): 1390-1402 (October 2023)Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition., , , , , , and . ACM Trans. Knowl. Discov. Data, 16 (4): 74:1-74:20 (2022)Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems., , , , , , , , , and . IEEE Trans. Knowl. Data Eng., 36 (2): 459-474 (February 2024)Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization., , , , , and . CoRR, (2021)AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation., , , , , , and . CoRR, (2024)Distributionally Robust Learning with Stable Adversarial Training., , , , , and . CoRR, (2021)Domain Generalization via Contrastive Causal Learning., , and . CoRR, (2022)ModelGPT: Unleashing LLM's Capabilities for Tailored Model Generation., , , , and . CoRR, (2024)Domain-Specific Bias Filtering for Single Labeled Domain Generalization., , , , , and . CoRR, (2021)Exploiting Contrastive Learning and Numerical Evidence for Improving Confusing Legal Judgment Prediction., , , , and . CoRR, (2022)