Learning Paradigms

Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics IJCAI 2024 Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains NeurIPS 2024 Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks AAAI 2024 Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization NeurIPS 2024 Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization AAAI 2024 TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts EMNLP 2024 Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning NeurIPS 2024 The Sample-Communication Complexity Trade-off in Federated Q-Learning NeurIPS 2024 The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential Recommendation NAACL 2024 Thinking Forward: Memory-Efficient Federated Finetuning of Language Models NeurIPS 2024 Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts CVPR 2024 Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NeurIPS 2024 Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning NeurIPS 2024 Towards Equipping Transformer with the Ability of Systematic Compositionality AAAI 2024 Towards Fair Graph Federated Learning via Incentive Mechanisms AAAI 2024 Towards Human-like Learning from Relational Structured Data AAAI 2024 Towards the Robustness of Differentially Private Federated Learning AAAI 2024 Towards Unified Task Embeddings Across Multiple Models: Bridging the Gap for Prompt-Based Large Language Models and Beyond ACL 2024 Traceable Federated Continual Learning CVPR 2024 Trace-of-Thought Prompting: Investigating Prompt-Based Knowledge Distillation Through Question Decomposition ACL 2024 Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning NeurIPS 2024 TransFed: A Way To Epitomize Focal Modulation Using Transformer-Based Federated Learning WACV 2024 Transfer Learning Using Inaccurate Physics Rule for Streamflow Prediction IJCAI 2024 TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients AAAI 2024 Two-stage LLM Fine-tuning with Less Specialization and More Generalization ICLR 2024