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NIPS
1997
13 years 11 months ago
Reinforcement Learning with Hierarchies of Machines
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Ronald Parr, Stuart J. Russell
WSCG
2004
130views more  WSCG 2004»
13 years 11 months ago
A Hybrid Approach to Rendering Handwritten Characters
With the growing popularity of pen-based computers comes the need to display clear handwritten characters at small sizes on low-resolution displays. This paper describes a method ...
Sara L. Su, Chenyu Wu, Ying-Qing Xu, Heung-Yeung S...
DATE
2009
IEEE
138views Hardware» more  DATE 2009»
14 years 4 months ago
Cache aware compression for processor debug support
—During post-silicon processor debugging, we need to frequently capture and dump out the internal state of the processor. Since internal state constitutes all memory elements, th...
Anant Vishnoi, Preeti Ranjan Panda, M. Balakrishna...
AAAI
2010
13 years 11 months ago
Bayesian Policy Search for Multi-Agent Role Discovery
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Aaron Wilson, Alan Fern, Prasad Tadepalli
ECIR
2009
Springer
13 years 7 months ago
Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis
Abstract. In the community of sentiment analysis, supervised learning techniques have been shown to perform very well. When transferred to another domain, however, a supervised sen...
Songbo Tan, Xueqi Cheng, Yuefen Wang, Hongbo Xu