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NIPS
1998
15 years 8 months ago
Global Optimisation of Neural Network Models via Sequential Sampling
We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
João F. G. de Freitas, Mahesan Niranjan, Ar...
JSA
2007
191views more  JSA 2007»
15 years 6 months ago
Automated memory-aware application distribution for Multi-processor System-on-Chips
Mapping of applications on a Multiprocessor System-on-Chip (MP-SoC) is a crucial step to optimize performance, energy and memory constraints at the same time. The problem is formu...
Heikki Orsila, Tero Kangas, Erno Salminen, Timo D....
HPDC
2008
IEEE
16 years 1 months ago
Issues in applying data mining to grid job failure detection and diagnosis
As grid computation systems become larger and more complex, manually diagnosing failures in jobs becomes impractical. Recently, machine-learning techniques have been proposed to d...
Lakshmikant Shrinivas, Jeffrey F. Naughton
HPDC
2007
IEEE
16 years 1 months ago
Ridge: combining reliability and performance in open grid platforms
Large-scale donation-based distributed infrastructures need to cope with the inherent unreliability of participant nodes. A widely-used work scheduling technique in such environme...
Krishnaveni Budati, Jason D. Sonnek, Abhishek Chan...
DIS
2007
Springer
16 years 25 days ago
Fast NML Computation for Naive Bayes Models
Abstract. The Minimum Description Length (MDL) is an informationtheoretic principle that can be used for model selection and other statistical inference tasks. One way to implement...
Tommi Mononen, Petri Myllymäki