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» Machine Learning by Function Decomposition
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ICML
2007
IEEE
16 years 2 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
ICML
2005
IEEE
16 years 2 months ago
High speed obstacle avoidance using monocular vision and reinforcement learning
We consider the task of driving a remote control car at high speeds through unstructured outdoor environments. We present an approach in which supervised learning is first used to...
Jeff Michels, Ashutosh Saxena, Andrew Y. Ng
110
Voted
ICML
2005
IEEE
16 years 2 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
ALT
2010
Springer
15 years 1 months ago
Recursive Teaching Dimension, Learning Complexity, and Maximum Classes
This paper is concerned with the combinatorial structure of concept classes that can be learned from a small number of examples. We show that the recently introduced notion of recu...
Thorsten Doliwa, Hans-Ulrich Simon, Sandra Zilles
ICML
2005
IEEE
16 years 2 months ago
Predicting probability distributions for surf height using an ensemble of mixture density networks
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...