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Meta-Learning

1524 directly classified papers

Papers per year

Papers

Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective AAAI 2021
Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning AAAI 2021
Cold-start Sequential Recommendation via Meta Learner AAAI 2021
Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation AAAI 2021
Bayesian Model-Agnostic Meta-Learning with Matrix-Valued Kernels for Quality Estimation ACL 2021
Multi-Pair Text Style Transfer for Unbalanced Data via Task-Adaptive Meta-Learning ACL 2021
Meta-Mining Discriminative Samples for Kinship Verification CVPR 2021
Semantic-Aware Knowledge Distillation for Few-Shot Class-Incremental Learning CVPR 2021
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach EMNLP 2021
Beyond Reptile: Meta-Learned Dot-Product Maximization between Gradients for Improved Single-Task Regularization EMNLP 2021
Meta Internal Learning NIPS 2021
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization NIPS 2021
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods NIPS 2021
Meta-Learning Sparse Implicit Neural Representations NIPS 2021
Learning-to-learn non-convex piecewise-Lipschitz functions NIPS 2021
Towards Zero-Shot Learning With Fewer Seen Class Examples WACV 2021
Camera Distortion-Aware 3D Human Pose Estimation in Video With Optimization-Based Meta-Learning ICCV 2021
Preference-Adaptive Meta-Learning for Cold-Start Recommendation IJCAI 2021
Uncertainty quantification using martingales for misspecified Gaussian processes ALT 2021
Learning sparse mixtures of permutations from noisy information COLT 2021
Fast and Efficient Locomotion via Learned Gait Transitions CORL 2021
The Task Specification Problem CORL 2021
Meta-Learning for Effective Multi-task and Multilingual Modelling EACL 2021
Power Constrained Bandits MLHC 2021
The Sample Complexity of Meta Sparse Regression AISTATS 2021