Learning parallel portfolios of algorithms
β Scribed by Marek Petrik; Shlomo Zilberstein
- Publisher
- Springer Netherlands
- Year
- 2007
- Tongue
- English
- Weight
- 440 KB
- Volume
- 48
- Category
- Article
- ISSN
- 1012-2443
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## a b s t r a c t We consider a parallel-machine scheduling problem with a learning effect and the makespan objective. The impact of the learning effect on job processing times is modelled by the general DeJong's learning curve. For this NP-hard problem we propose two exact algorithms: a sequenti
In [2], a parallel perceptron learning algorithm on the single-channel broadcast communication model was proposed to speed up the learning of weights of perceptrons [3]. The results in [2] showed that given n training examples, the average speedup is 1.48\*n~ n by n processors. Here, we explain how