Meta-Learning

Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability AAAI 2023 The Effect of Diversity in Meta-Learning AAAI 2023 Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning ICLR 2023 Thompson Sampling with Diffusion Generative Prior ICML 2023 Towards Low-Resource Automatic Program Repair with Meta-Learning and Pretrained Language Models EMNLP 2023 Towards Omni-generalizable Neural Methods for Vehicle Routing Problems ICML 2023 Towards Reliable Neural Machine Translation with Consistency-Aware Meta-Learning AAAI 2023 Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework AISTATS 2023 Transformers as Algorithms: Generalization and Stability in In-context Learning ICML 2023 UniSumm and SummZoo: Unified Model and Diverse Benchmark for Few-Shot Summarization ACL 2023 Unsupervised Learning for Combinatorial Optimization Needs Meta Learning ICLR 2023 Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning ICLR 2023 Zero- and Few-Shot Event Detection via Prompt-Based Meta Learning ACL 2023 Zero-Cost Operation Scoring in Differentiable Architecture Search AAAI 2023 Zero-shot causal learning NeurIPS 2023 Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization NeurIPS 2023 ZiCo: Zero-shot NAS via inverse Coefficient of Variation on Gradients ICLR 2023 A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases NeurIPS 2022 A contrastive rule for meta-learning NeurIPS 2022 Active Bayesian Causal Inference NeurIPS 2022 AdaCat: Adaptive categorical discretization for autoregressive models UAI 2022 Adapting to Mixing Time in Stochastic Optimization with Markovian Data ICML 2022 Adaptive Model Predictive Control by Learning Classifiers L4DC 2022 Adapt to Environment Sudden Changes by Learning a Context Sensitive Policy AAAI 2022 Adversarial Task Up-sampling for Meta-learning NeurIPS 2022