509 search results - page 74 / 102 » Using Learning for Approximation in Stochastic Processes |
126
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ATAL
2009
Springer
15 years 9 months ago
2009
Springer
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
135
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ACL
2006
15 years 3 months ago
2006
In this paper we report our work on building a POS tagger for a morphologically rich language- Hindi. The theme of the research is to vindicate the stand that- if morphology is st...
121
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ILP
2007
Springer
15 years 8 months ago
2007
Springer
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
145
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AAAI
2006
15 years 3 months ago
2006
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
135
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KDD
2010
ACM
15 years 6 months ago
2010
ACM
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...