We propose new methods to exploit contemporaneous text, such as on-line news articles, to improve language models for automatic speech recognition and other natural language proce...
In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...
ended abstract summarizes the research presented in Dr. Pardoe’s recently-completed Ph.D. thesis [Pardoe 2011]. The thesis considers how adaptive trading agents can take advantag...