We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
Learning to build and test virtual reality (VR) systems is difficult due to the many required knowledge (e.g. computer graphics, sound processing, simulation, interaction, etc.) an...
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...