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Meta-Learning

357 directly classified papers

Papers per year

Papers

Dataset Distillation using Neural Feature Regression NIPS 2022
Understanding Benign Overfitting in Gradient-Based Meta Learning NIPS 2022
Modeling Human Exploration Through Resource-Rational Reinforcement Learning NIPS 2022
Meta-Complementing the Semantics of Short Texts in Neural Topic Models NIPS 2022
Efficient Riemannian Meta-Optimization by Implicit Differentiation AAAI 2022
Leaping through Time with Gradient-Based Adaptation for Recommendation AAAI 2022
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks AAAI 2022
Introducing Symmetries to Black Box Meta Reinforcement Learning AAAI 2022
Learning Not to Learn: Nature versus Nurture In Silico AAAI 2022
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation ACL 2022
MetaWeighting: Learning to Weight Tasks in Multi-Task Learning ACL 2022
Efficiently Tuned Parameters Are Task Embeddings EMNLP 2022
SAT: Improving Semi-Supervised Text Classification with Simple Instance-Adaptive Self-Training EMNLP 2022
Efficient and Modular Implicit Differentiation NIPS 2022
On the Convergence Theory for Hessian-Free Bilevel Algorithms NIPS 2022
Few-Shot Fast-Adaptive Anomaly Detection NIPS 2022
Test Time Adaptation via Conjugate Pseudo-labels NIPS 2022
Gradient Descent: The Ultimate Optimizer NIPS 2022
Discovered Policy Optimisation NIPS 2022
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach NIPS 2022
Multi-agent Dynamic Algorithm Configuration NIPS 2022
Task-level Differentially Private Meta Learning NIPS 2022
DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems NIPS 2022
Exploring Example Influence in Continual Learning NIPS 2022
Enhanced Bilevel Optimization via Bregman Distance NIPS 2022