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AAAI
2006
14 years 11 months ago
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
AAAI
1998
14 years 11 months ago
Supermodels and Robustness
When search techniques are used to solve a practical problem, the solution produced is often brittle in the sense that small execution difficulties can have an arbitrarily large e...
Matthew L. Ginsberg, Andrew J. Parkes, Amitabha Ro...
AAAI
2000
14 years 11 months ago
Generalizing Boundary Points
The complexity of numerical domain partitioning depends on the number of potential cut points. In multiway partitioning this dependency is often quadratic, even exponential. There...
Tapio Elomaa, Juho Rousu
AAAI
1998
14 years 11 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Adam J. Grove, Dale Schuurmans
AAAI
2000
14 years 11 months ago
TCBB Scheme: Applications to Single Machine Job Sequencing Problems
Transpose-and-Cache Branch-and-Bound (TCBB) has shown promise in solving large single machine quadratic penalty problems. There exist other classes of single machine job sequencin...
Sakib A. Mondal, Anup K. Sen