Meta-Learning

Adaptive Compositional Continual Meta-Learning ICML 2023 AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer CoRL 2023 Adversarial Online Multi-Task Reinforcement Learning ALT 2023 Algorithm Selection for Deep Active Learning with Imbalanced Datasets NeurIPS 2023 AlphaD3M: An Open-Source AutoML Library for Multiple ML Tasks AutoML 2023 A Meta-Learning Approach to Predicting Performance and Data Requirements CVPR 2023 A Meta-Reinforcement Learning Algorithm for Causal Discovery CLeaR 2023 An Erudite Fine-Grained Visual Classification Model CVPR 2023 A Neural Span-Based Continual Named Entity Recognition Model AAAI 2023 A Partially-Supervised Reinforcement Learning Framework for Visual Active Search NeurIPS 2023 Architecture, Dataset and Model-Scale Agnostic Data-Free Meta-Learning CVPR 2023 Are Deep Neural Networks SMARTer Than Second Graders? CVPR 2023 A Simple Recipe to Meta-Learn Forward and Backward Transfer ICCV 2023 A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm NeurIPS 2023 AutoKeras: An AutoML Library for Deep Learning JMLR 2023 AutoSTL: Automated Spatio-Temporal Multi-Task Learning AAAI 2023 Backdoor Defense via Adaptively Splitting Poisoned Dataset CVPR 2023 Balanced Meta Learning and Diverse Sampling for Lifelong Task-Oriented Dialogue Systems AAAI 2023 Balanced Mixture of Supernets for Learning the CNN Pooling Architecture AutoML 2023 BETA-CD: A Bayesian Meta-Learned Cognitive Diagnosis Framework for Personalized Learning AAAI 2023 Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance CoRL 2023 Bridge the Inference Gaps of Neural Processes via Expectation Maximization ICLR 2023 Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? ICML 2023 CLUTR: Curriculum Learning via Unsupervised Task Representation Learning ICML 2023 Combinatorial Causal Bandits AAAI 2023