Meta-Learning

Information-theoretic Task Selection for Meta-Reinforcement Learning NeurIPS 2020 Intent Preference Decoupling for User Representation on Online Recommender System IJCAI 2020 iTAML: An Incremental Task-Agnostic Meta-learning Approach CVPR 2020 Learning Efficient Task-Specific Meta-Embeddings with Word Prisms COLING 2020 Learning Fast Adaptation on Cross-Accented Speech Recognition Interspeech 2020 Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks AAAI 2020 Learning Graph Convolutional Network for Skeleton-Based Human Action Recognition by Neural Searching AAAI 2020 Learning Invariants through Soft Unification NeurIPS 2020 Learning Low-Resource End-To-End Goal-Oriented Dialog for Fast and Reliable System Deployment ACL 2020 Learning Meta Model for Zero- and Few-Shot Face Anti-Spoofing AAAI 2020 Learning to Adapt to Evolving Domains NeurIPS 2020 Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks ICLR 2020 Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks ACL 2020 Learning to Forget for Meta-Learning CVPR 2020 Learning to Learn by Zeroth-Order Oracle ICLR 2020 Learning to Learn Cropping Models for Different Aspect Ratio Requirements CVPR 2020 Learning to learn generative programs with Memoised Wake-Sleep UAI 2020 Learning to Learn Kernels with Variational Random Features ICML 2020 Learning to Learn Morphological Inflection for Resource-Poor Languages AAAI 2020 Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation EMNLP 2020 Learning to Learn Variational Semantic Memory NeurIPS 2020 Learning to Learn with Feedback and Local Plasticity NeurIPS 2020 Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees AAAI 2020 Learning to Select Best Forecast Tasks for Clinical Outcome Prediction NeurIPS 2020 Learning to Transfer: Unsupervised Domain Translation via Meta-Learning AAAI 2020