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Meta-Learning

1,529 papers

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Papers

A Meta-Learning Perspective on Cold-Start Recommendations for Items NIPS 2017
An Empirical Bayes Approach to Optimizing Machine Learning Algorithms NIPS 2017
Multi-Information Source Optimization NIPS 2017
From Bayesian Sparsity to Gated Recurrent Nets NIPS 2017
Stochastic Rank-1 Bandits AISTATS 2017
Discovering and Exploiting Additive Structure for Bayesian Optimization AISTATS 2017
Fast Video Classification via Adaptive Cascading of Deep Models CVPR 2017
Learning to Learn From Noisy Web Videos CVPR 2017
Learning Algorithms for Active Learning ICML 2017
Neural Optimizer Search with Reinforcement Learning ICML 2017
Learning to Learn without Gradient Descent by Gradient Descent ICML 2017
AdaNet: Adaptive Structural Learning of Artificial Neural Networks ICML 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks ICML 2017
Bayesian Optimization with Tree-structured Dependencies ICML 2017
Meta Networks ICML 2017
Learning to Learn Programs from Examples: Going Beyond Program Structure IJCAI 2017
Online Multitask Relative Similarity Learning IJCAI 2017
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning IJCAI 2017
Stacking With Auxiliary Features IJCAI 2017
Discretized Continuous Speech Emotion Recognition with Multi-Task Deep Recurrent Neural Network INTERSPEECH 2017
Learning Scalable Deep Kernels with Recurrent Structure JMLR 2017
Accurately and Efficiently Interpreting Human-Robot Instructions of Varying Granularities RSS 2017
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization NIPS 2016
Learning feed-forward one-shot learners NIPS 2016
Adaptive Smoothed Online Multi-Task Learning NIPS 2016