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Meta-Learning

1524 directly classified papers

Papers per year

Papers

From Bayesian Sparsity to Gated Recurrent Nets NIPS 2017
Neural Program Meta-Induction NIPS 2017
A Meta-Learning Perspective on Cold-Start Recommendations for Items NIPS 2017
An Empirical Bayes Approach to Optimizing Machine Learning Algorithms NIPS 2017
Discovering and Exploiting Additive Structure for Bayesian Optimization AISTATS 2017
Zap Q-Learning NIPS 2017
Learning to Model the Tail NIPS 2017
Meta Networks ICML 2017
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning IJCAI 2017
Fast Video Classification via Adaptive Cascading of Deep Models CVPR 2017
Stochastic Rank-1 Bandits AISTATS 2017
AdaNet: Adaptive Structural Learning of Artificial Neural Networks ICML 2017
Online Multitask Relative Similarity Learning IJCAI 2017
Learning to Learn without Gradient Descent by Gradient Descent ICML 2017
Accurately and Efficiently Interpreting Human-Robot Instructions of Varying Granularities RSS 2017
Neural Optimizer Search with Reinforcement Learning ICML 2017
Stacking With Auxiliary Features IJCAI 2017
GLASSES: Relieving The Myopia Of Bayesian Optimisation AISTATS 2016
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization NIPS 2016
Adaptive Smoothed Online Multi-Task Learning NIPS 2016
Meta-Learning with Memory-Augmented Neural Networks ICML 2016
TPOT: A Tree-based Pipeline Optimization Tool for Automating Machine Learning AUTOML 2016
Towards Automatically-Tuned Neural Networks AUTOML 2016
A Brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning Without Human Intervention AUTOML 2016
The Role of Intrinsic Motivation in Artificial Language Emergence: a Case Study on Colour COLING 2016