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» Using Machine Learning Techniques to Interpret WH-questions
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ICML
2002
IEEE
16 years 2 months ago
Action Refinement in Reinforcement Learning by Probability Smoothing
In many reinforcement learning applications, the set of possible actions can be partitioned by the programmer into subsets of similar actions. This paper presents a technique for ...
Carles Sierra, Dídac Busquets, Ramon L&oacu...
ALT
2002
Springer
15 years 10 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
NIPS
2001
15 years 2 months ago
Adaptive Sparseness Using Jeffreys Prior
In this paper we introduce a new sparseness inducing prior which does not involve any (hyper)parameters that need to be adjusted or estimated. Although other applications are poss...
Mário A. T. Figueiredo
ICML
2009
IEEE
16 years 2 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
ICALT
2003
IEEE
15 years 6 months ago
An Intelligent Tutoring System Prototype for Learning to Program Java?
The “JavaTM Intelligent Tutoring System” (JITS) research project involves the development of a programming tutor designed for students in their first programming course in Jav...
Edward R. Sykes