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Meta-Learning

1,719 papers

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Papers

Sharing Knowledge for Meta-learning with Feature Descriptions NeurIPS 2022 Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning ICML 2022 SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization JMLR 2022 Starting from “Zero”: An Incremental Zero-shot Learning Approach for Assessing Peer Feedback Comments NAACL 2022 ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning UAI 2022 Subspace Learning for Effective Meta-Learning ICML 2022 SUMNAS: Supernet with Unbiased Meta-Features for Neural Architecture Search ICLR 2022 System-Agnostic Meta-Learning for MDP-based Dynamic Scheduling via Descriptive Policy AISTATS 2022 Task Affinity with Maximum Bipartite Matching in Few-Shot Learning ICLR 2022 Task-level Differentially Private Meta Learning NeurIPS 2022 TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding AACL 2022 Task Relatedness-Based Generalization Bounds for Meta Learning ICLR 2022 Teaching Interactively to Learn Emotions in Natural Language NAACL 2022 Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning JMLR 2022 The Role of Deconfounding in Meta-learning ICML 2022 Thompson Sampling for Bandit Learning in Matching Markets IJCAI 2022 Towards Few-Shot Identification of Morality Frames using In-Context Learning EMNLP 2022 Towards Learning Universal Hyperparameter Optimizers with Transformers NeurIPS 2022 Transferability and Stability of Learning with Limited Labelled Data in Multilingual Text Document Classification IJCAI 2022 Transferring Hierarchical Structures with Dual Meta Imitation Learning CoRL 2022 Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling ICML 2022 Transformers are Meta-Reinforcement Learners ICML 2022 Triangulation candidates for Bayesian optimization NeurIPS 2022 Using natural language and program abstractions to instill human inductive biases in machines NeurIPS 2022 VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty ICML 2022