AAAI
2007
14 years 1 months ago
2007
We consider problems of geometric exploration and selfdeployment for simple robots that can only sense the combinatorial (non-metric) features of their surroundings. Even with suc...
AAAI
2008
14 years 1 months ago
2008
We consider the following setting: a decision maker must make a decision based on reported data points with binary labels. Subsets of data points are controlled by different selfi...
AAAI
2007
14 years 1 months ago
2007
Recent studies have shown that graph-based approaches are effective for semi-supervised learning. The key idea behind many graph-based approaches is to enforce the consistency bet...
AAAI
2008
14 years 1 months ago
2008
Security at major locations of economic or political importance is a key concern around the world, particularly given the threat of terrorism. Limited security resources prevent f...
AAAI
2007
14 years 1 months ago
2007
We propose a novel kernel regression algorithm which takes into account order preferences on unlabeled data. Such preferences have the form that point x1 has a larger target value...
AAAI
2008
14 years 1 months ago
2008
This paper summarizes recent advances in the application of multiagent coordination algorithms to air traffic flow management. Indeed, air traffic flow management is one of the fu...
AAAI
2007
14 years 1 months ago
2007
Our work links Chinese calligraphy to computer science through an integrated intelligence approach. We first extract strokes of existent calligraphy using a semi-automatic, twoph...
AAAI
2008
14 years 1 months ago
2008
Hybrid Scheduling Problems (HSPs) contain both temporal and finite-domain variables, as well as constraints between them. A hybrid constraint over temporal and finite-domain varia...
AAAI
2007
14 years 1 months ago
2007
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
AAAI
2007
14 years 1 months ago
2007
Consistencies are properties of Constraint Networks (CNs) that can be exploited in order to make inferences. When a significant amount of such inferences can be performed, CNs ar...