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NIPS
2003
15 years 7 months ago
Policy Search by Dynamic Programming
We consider the policy search approach to reinforcement learning. We show that if a “baseline distribution” is given (indicating roughly how often we expect a good policy to v...
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff...
NIPS
2007
15 years 7 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
148
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APSEC
2002
IEEE
15 years 11 months ago
Lessons Learned in Framework-Based Software Process Improvement
Software process improvement (SPI) has emerged as a critical area for organizations involved in software development. There is now considerable evidence that SPI can provide subst...
Pankaj Jalote
NIPS
1993
15 years 7 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
UM
2001
Springer
15 years 10 months ago
Investigating Students' Self-Assessment Skills
: Student modeling approaches predominantly focus on modeling student knowledge. For effective learning, however, it is necessary to teach students how to learn, as well as to prov...
Antonija Mitrovic