Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
While paraphrasing is critical both for interpretation and generation of natural language, current systems use manual or semi-automatic methods to collect paraphrases. We present ...
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Program dynamic optimization, adaptive to runtime behavior changes, has become increasingly important for both performance and energy savings. However, most runtime optimizations o...
Mobile robots must cope with uncertainty from many sources along the path from interpreting raw sensor inputs to behavior selection to execution of the resulting primitive actions...
Peter Stone, Mohan Sridharan, Daniel Stronger, Gre...