NIPS
2007
14 years 26 days ago
2007
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
NIPS
2007
14 years 26 days ago
2007
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
NIPS
2007
14 years 26 days ago
2007
In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
NIPS
2007
14 years 26 days ago
2007
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
NETWORKING
2007
14 years 26 days ago
2007
We consider event dependent routing algorithms for on-line explicit source routing in MPLS networks. The proposed methods are based on load shared sequential routing in which load ...
NIPS
2008
14 years 26 days ago
2008
We present cutoff averaging, a technique for converting any conservative online learning algorithm into a batch learning algorithm. Most online-to-batch conversion techniques work...
IJCAI
2007
14 years 26 days ago
2007
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
ICONIP
2007
14 years 27 days ago
2007
One of the authors has proposed a simple learning algorithm for recurrent neural networks, which requires computational cost and memory capacity in practical order O(n2 )[1]. The a...
ICMLA
2008
14 years 27 days ago
2008
We report on three distinct experiments that provide new valuable insights into learning algorithms and datasets. We first describe two effective meta-features that significantly ...
ICMLA
2008
14 years 27 days ago
2008
We are interested in learning an adaptive local metric on a lower dimensional manifold for query