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Meta-Learning

1524 directly classified papers

Papers per year

Papers

Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning AISTATS 2021
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving ICCV 2021
Function Contrastive Learning of Transferable Meta-Representations ICML 2021
Debiasing Model Updates for Improving Personalized Federated Training ICML 2021
Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising Model MIDL 2021
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL NIPS 2021
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning NIPS 2021
LIORI at SemEval-2021 Task 8: Ask Transformer for measurements ACL 2021
Information-theoretic Task Selection for Meta-Reinforcement Learning NIPS 2020
Meta-Learning through Hebbian Plasticity in Random Networks NIPS 2020
Gradient-EM Bayesian Meta-Learning NIPS 2020
ANA at SemEval-2020 Task 4: MUlti-task learNIng for cOmmonsense reasoNing (UNION) SEMEVAL 2020
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning NIPS 2020
Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge IJCAI 2020
OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation UAI 2020
Learning to learn generative programs with Memoised Wake-Sleep UAI 2020
From WiscKey to Bourbon: A Learned Index for Log-Structured Merge Trees OSDI 2020
Meta-learning from Tasks with Heterogeneous Attribute Spaces NIPS 2020
The Importance of the Test Set Size in Quantification Assessment IJCAI 2020
Multitask Soft Option Learning UAI 2020
MELD: Meta-Reinforcement Learning from Images via Latent State Models CORL 2020
MetAL: Active Semi-Supervised Learning on Graphs via Meta-Learning ACML 2020
Learning to Select Best Forecast Tasks for Clinical Outcome Prediction NIPS 2020
Learning Invariants through Soft Unification NIPS 2020
Multi-Task Supervised Pretraining for Neural Domain Adaptation ACL 2020