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» Machine Learning by Function Decomposition
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BMCBI
2008
112views more  BMCBI 2008»
15 years 2 months ago
A simplified approach to disulfide connectivity prediction from protein sequences
Background: Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on differen...
Marc Vincent, Andrea Passerini, Matthieu Labb&eacu...
COLT
1992
Springer
15 years 6 months ago
On Learning Limiting Programs
Machine learning of limit programs (i.e., programs allowed finitely many mind changes about their legitimate outputs) for computable functions is studied. Learning of iterated lim...
John Case, Sanjay Jain, Arun Sharma
ECML
2006
Springer
15 years 5 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
ICML
2005
IEEE
16 years 2 months ago
Beyond the point cloud: from transductive to semi-supervised learning
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
Vikas Sindhwani, Partha Niyogi, Mikhail Belkin
ATAL
2009
Springer
15 years 8 months ago
MABLE: a framework for learning from natural instruction
The Modular Architecture for Bootstrapped Learning Experiments (MABLE) is a system that is being developed to allow humans to teach computers in the most natural manner possible: ...
Roger Mailler, Daniel Bryce, Jiaying Shen, Ciaran ...