Proceedings of the 26th Annual International Conference on Machine Learning

By Andrea Pohoreckyj Danyluk, Léon Bottou, Michael L. Littman. 2009

133 citations recorded by the source corpus.

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Citations in the corpus

Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models (2015, methodology): “Prior work has suggested a variety of different novelty functions e.g., [1, 2] based on state visitation frequency.”
A Deep Hierarchical Approach to Lifelong Learning in Minecraft (2016, background): “Our work can also be interpreted as a form of curriculum learning [Bengio et al., 2009] for RL.”
Charagram: Embedding Words and Sentences via Character n-grams (2016, neutral): “This is similar to curriculum learning (Bengio et al., 2009).”
Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering (2015, background): “Then ||S − S l || ≤ (l + 1) n i=l+1 λ i (11) Fact 2 [Kumar et al., 2009a] With some probability 1 − p or higher, we can write the following inequality: || S l − S m || ≤ ||S − S m || + nS max 4 64m l 1 + wd * S S max 1 2 (12) Then, adding both sides of Eq.11 and Eq.12, noting that n i=m+1 ≥ n i=l+1…”
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning (2017, background): “Finally, curriculum learning has also been explored in the context of supervised learning [Bengio et al., 2009].”
The Role of Typicality in Object Classification: Improving The Generalization Capacity of Convolutional Neural Networks (2016, methodology): “There are some prior works on finding the right features [Blum and Langley, 1997], choosing the appropriate train set and how to order training examples for learning better classifiers [Bengio et al., 2009].”
Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework for Multiview Clustering and Semi-Supervised Classification (2016, methodology): “[Chaudhuri et al., 2009] projected the data into a lower dimensional subspace and clustered multiview data via canonical correlation analysis.”