82 search results - page 7 / 17 » MDPs: Learning in Varying Environments |
APSEC
2004
IEEE
14 years 1 months ago
2004
IEEE
Pair programmers need a "warmup phase" before the pair can work at full speed. The length of the learning interval varies, depending on how experienced the developers are...
MCS
2009
Springer
14 years 2 months ago
2009
Springer
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
ECTEL
2006
Springer
14 years 1 months ago
2006
Springer
This paper presents a short overview of blended learning, showing arguments for and against these concepts. Potential blended learning scenarios are described that vary depending o...
UAI
2008
13 years 11 months ago
2008
Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinfor...
ICPR
2006
IEEE
14 years 11 months ago
2006
IEEE
Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this pa...