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ICANN
2009
Springer
14 years 11 days ago
Learning Complex Population-Coded Sequences
The sequential structure of complex actions is apparently at an abstract “cognitive” level in several regions of the frontal cortex, independent of the control of the immediate...
Kiran V. Byadarhaly, Mithun Perdoor, Suresh Vasa, ...
ECML
2007
Springer
13 years 9 months ago
Sequence Labeling with Reinforcement Learning and Ranking Algorithms
Many problems in areas such as Natural Language Processing, Information Retrieval, or Bioinformatic involve the generic task of sequence labeling. In many cases, the aim is to assi...
Francis Maes, Ludovic Denoyer, Patrick Gallinari
NIPS
2007
13 years 9 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
ICMLA
2010
13 years 5 months ago
Robust Learning for Adaptive Programs by Leveraging Program Structure
Abstract--We study how to effectively integrate reinforcement learning (RL) and programming languages via adaptation-based programming, where programs can include non-deterministic...
Jervis Pinto, Alan Fern, Tim Bauer, Martin Erwig
JMLR
2010
121views more  JMLR 2010»
13 years 2 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor