Sciweavers

6 search results - page 1 / 2
» Can good learners always compensate for poor learners
Sort
View
ATAL
2006
Springer
13 years 6 months ago
Can good learners always compensate for poor learners?
Can a good learner compensate for a poor learner when paired in a coordination game? Previous work has given an example where a special learning algorithm (FMQ) is capable of doin...
Keith Sullivan, Liviu Panait, Gabriel Catalin Bala...
WMTE
2006
IEEE
13 years 10 months ago
The Focus Problem in Mobile Learning
Mobile learning has a lot of potential for supporting learning in situations such as in a museum, at a tourist sight or when exploring biological phenomena at a riverside. There l...
Christoph Göth, Dirk Frohberg, Gerhard Schwab...
UAI
2008
13 years 5 months ago
Learning Arithmetic Circuits
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
Daniel Lowd, Pedro Domingos
AAAI
2006
13 years 5 months ago
Anytime Induction of Decision Trees: An Iterative Improvement Approach
Most existing decision tree inducers are very fast due to their greedy approach. In many real-life applications, however, we are willing to allocate more time to get better decisi...
Saher Esmeir, Shaul Markovitch
AINA
2010
IEEE
13 years 9 months ago
Iterative Route Discovery in AODV
Abstract—Several protocols for ad hoc network try to reduce redundancy as an effective measure against broadcast problems. Though these protocols ensure good performance in a fav...
Nashid Shahriar, Syed Ashker Ibne Mujib, Arup Rato...