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1803.02999
Cited By
On First-Order Meta-Learning Algorithms
8 March 2018
Alex Nichol
Joshua Achiam
John Schulman
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Papers citing
"On First-Order Meta-Learning Algorithms"
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Title
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Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
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Qi Chen
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Few-Shot Classification with Contrastive Learning
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Jinghua Wang
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SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction
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Federated Meta-Learning for Traffic Steering in O-RAN
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Online Continual Learning via the Meta-learning Update with Multi-scale Knowledge Distillation and Data Augmentation
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Adaptive Meta-learner via Gradient Similarity for Few-shot Text Classification
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Transductive Decoupled Variational Inference for Few-Shot Classification
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Meta Learning for High-dimensional Ising Model Selection Using
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Transformers as Meta-Learners for Implicit Neural Representations
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Gradient-based Bi-level Optimization for Deep Learning: A Survey
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Kernel Relative-prototype Spectral Filtering for Few-shot Learning
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Meta Spatio-Temporal Debiasing for Video Scene Graph Generation
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Meta-Registration: Learning Test-Time Optimization for Single-Pair Image Registration
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MetaComp: Learning to Adapt for Online Depth Completion
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Heuristic-free Optimization of Force-Controlled Robot Search Strategies in Stochastic Environments
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Few-shot bioacoustic event detection at the DCASE 2022 challenge
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Generating Pseudo-labels Adaptively for Few-shot Model-Agnostic Meta-Learning
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Few 'Zero Level Set'-Shot Learning of Shape Signed Distance Functions in Feature Space
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Few-Example Clustering via Contrastive Learning
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Adaptive Personlization in Federated Learning for Highly Non-i.i.d. Data
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Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners
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Invariant and Transportable Representations for Anti-Causal Domain Shifts
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The least-control principle for local learning at equilibrium
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Dynamic Sub-Cluster-Aware Network for Few-Shot Skin Disease Classification
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Prompting Decision Transformer for Few-Shot Policy Generalization
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Understanding Benign Overfitting in Gradient-Based Meta Learning
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Leveraging Language for Accelerated Learning of Tool Manipulation
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Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
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...
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