We introduce a variational approach to image segmentation based on sparse coverings of image domains by shape templates. The objective function combines a data term that achieves ...
Dirk Breitenreicher, Jan Lellmann, Christoph Schn&...
We describe a robot system that autonomously acquires skills through interaction with its environment. The robot learns to sequence the execution of a set of innate controllers to...
George Konidaris, Scott Kuindersma, Roderic A. Gru...
In environmental and natural resource planning domains actions are taken at a large number of locations over multiple time periods. These problems have enormous state and action s...
In this paper, we model the pair-wise similarities of a set of documents as a weighted network with a single cutoff parameter. Such a network can be thought of an ensemble of unwe...
In this paper, we propose a novel method to select the most informative subset of features, which has little redundancy and very strong discriminating power. Our proposed approach...
Si Liu, Hairong Liu, Longin Jan Latecki, Shuicheng...
A general game player automatically learns to play arbitrary new games solely by being told their rules. For this purpose games are specified in the game description language GDL...
We propose Tree Sequence Kernel (TSK), which implicitly exhausts the structure features of a sequence of subtrees embedded in the phrasal parse tree. By incorporating the capabili...
Selection bias, caused by preferential exclusion of samples from the data, is a major obstacle to valid causal and statistical inferences; it cannot be removed by randomized exper...
This paper extends existing plan recognition research to handle plans containing loops. We supply an encoding of plans with loops for recognition, based on techniques used to pars...
Automated agents for electricity markets, social networks, and other distributed networks must repeatedly interact with other intelligent agents, often without observing associate...
Jacob W. Crandall, Asad Ahmed, Michael A. Goodrich