Meta-Learning

A Meta-Learning Approach for Custom Model Training AAAI 2019 AutoLoss: Learning Discrete Schedule for Alternate Optimization ICLR 2019 Bayesian Functional Optimisation with Shape Prior AAAI 2019 Blending-Target Domain Adaptation by Adversarial Meta-Adaptation Networks CVPR 2019 Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies? IJCAI 2019 Compositional generalization through meta sequence-to-sequence learning NeurIPS 2019 Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes AISTATS 2019 Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing ACL 2019 Cross Attention Network for Few-shot Classification NeurIPS 2019 Discovery of Useful Questions as Auxiliary Tasks NeurIPS 2019 Efficient Meta Learning via Minibatch Proximal Update NeurIPS 2019 Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes NeurIPS 2019 Feature-Critic Networks for Heterogeneous Domain Generalization ICML 2019 Few-Shot Learning With Localization in Realistic Settings CVPR 2019 Few-Shot Representation Learning for Out-Of-Vocabulary Words ACL 2019 GumDrop at the DISRPT2019 Shared Task: A Model Stacking Approach to Discourse Unit Segmentation and Connective Detection NAACL 2019 HyperAdam: A Learnable Task-Adaptive Adam for Network Training AAAI 2019 Image Deformation Meta-Networks for One-Shot Learning CVPR 2019 Induction Networks for Few-Shot Text Classification EMNLP 2019 Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks EMNLP 2019 Learning Options with Interest Functions AAAI 2019 Learning to Generalize from Sparse and Underspecified Rewards ICML 2019 Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification EMNLP 2019 Learning to Learn By Self-Critique NeurIPS 2019 Learning to Learn From Noisy Labeled Data CVPR 2019