Co-occurring keywords · papers mentioning both
Papers
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory
AISTATS 2025
Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation
ICLR 2024
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
NeurIPS 2024
XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task Coverage
AISTATS 2024
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
NeurIPS 2024
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
NeurIPS 2023
Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning
NeurIPS 2023
Powderworld: A Platform for Understanding Generalization via Rich Task Distributions
ICLR 2023
Recurrent Hypernetworks are Surprisingly Strong in Meta-RL
NeurIPS 2023
Risk-aware curriculum generation for heavy-tailed task distributions
UAI 2023
The Effect of Diversity in Meta-Learning
AAAI 2023
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation
NeurIPS 2022
Curriculum Reinforcement Learning via Constrained Optimal Transport
ICML 2022
Distributionally Adaptive Meta Reinforcement Learning
NeurIPS 2022
How to Distribute Data across Tasks for Meta-Learning?
AAAI 2022
Meta Learning MDPs with linear transition models
AISTATS 2022
Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach
NeurIPS 2022
ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning
UAI 2022
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP
EMNLP 2021
Evaluating Meta-Reinforcement Learning through a HVAC Control Benchmark (Student Abstract)
AAAI 2021
Learning Task-Distribution Reward Shaping with Meta-Learning
AAAI 2021
Meta Learning on a Sequence of Imbalanced Domains With Difficulty Awareness
ICCV 2021
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning
NeurIPS 2021
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
NeurIPS 2021
Meta-learning with Stochastic Linear Bandits
ICML 2020