Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Moon...
One way for agents to reach a joint decision is to vote over the alternatives. In open, anonymous settings such as the Internet, an agent can vote more than once without being det...
Various problems in AI and multiagent systems can be tackled by finding the “most desirable” elements of a set given some binary relation. Examples can be found in areas as d...
ar for abstract concepts, and a number of formally expressed, structural restrictions. Copyright c 2008, Association for the Advancement of Artificial Intelligence (www.aaai.org). ...
We present a novel application of structured classification: identifying function entry points (FEPs, the starting byte of each function) in program binaries. Such identification ...
Nathan E. Rosenblum, Xiaojin Zhu, Barton P. Miller...
The automated planning community has traditionally focused on the efficient synthesis of plans given a complete domain theory. In the past several years, this line of work met wi...
ion-Based Versus Potential-Aware Automated Abstraction in Imperfect Information Games: An Experimental Comparison Using Poker Andrew Gilpin and Tuomas Sandholm Computer Science Dep...
RDF (“Resource Description Framework”) is now a widely used World Wide Web Consortium standard. However, methods to index large volumes of RDF data are still in their infancy....
Octavian Udrea, Andrea Pugliese, V. S. Subrahmania...
The idea of local learning, i.e., classifying a particular example based on its neighbors, has been successfully applied to many semi-supervised and clustering problems recently. ...