Sciweavers

1393 search results - page 55 / 279
» Machine Learning by Function Decomposition
Sort
View
ICML
2003
IEEE
16 years 2 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
ARTMED
1999
92views more  ARTMED 1999»
15 years 1 months ago
Two-Stage Machine Learning model for guideline development
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....
CHES
2011
Springer
240views Cryptology» more  CHES 2011»
14 years 1 months ago
Lightweight and Secure PUF Key Storage Using Limits of Machine Learning
A lightweight and secure key storage scheme using silicon Physical Unclonable Functions (PUFs) is described. To derive stable PUF bits from chip manufacturing variations, a lightwe...
Meng-Day (Mandel) Yu, David M'Raïhi, Richard ...
DATE
2010
IEEE
185views Hardware» more  DATE 2010»
15 years 6 months ago
Fault diagnosis of analog circuits based on machine learning
— We discuss a fault diagnosis scheme for analog integrated circuits. Our approach is based on an assemblage of learning machines that are trained beforehand to guide us through ...
Ke Huang, Haralampos-G. D. Stratigopoulos, Salvado...
ESOP
2011
Springer
14 years 5 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...