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ESANN
2007
13 years 10 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
NN
2006
Springer
13 years 8 months ago
Propagation and control of stochastic signals through universal learning networks
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
Kotaro Hirasawa, Shingo Mabu, Jinglu Hu
NIPS
1994
13 years 10 months ago
On-line Learning of Dichotomies
The performance of on-line algorithms for learning dichotomies is studied. In on-line learning, the number of examples P is equivalent to the learning time, since each example is ...
N. Barkai, H. Sebastian Seung, Haim Sompolinsky
COLT
2008
Springer
13 years 10 months ago
Polynomial Regression under Arbitrary Product Distributions
In recent work, Kalai, Klivans, Mansour, and Servedio [KKMS05] studied a variant of the "Low-Degree (Fourier) Algorithm" for learning under the uniform probability distr...
Eric Blais, Ryan O'Donnell, Karl Wimmer
ICDAR
2009
IEEE
13 years 6 months ago
Document Image Binarisation Using Markov Field Model
This paper presents a new approach for the binarization of seriously degraded manuscript. We introduce a new technique based on a Markov Random Field (MRF) model of the document. ...
Thibault Lelore, Frédéric Bouchara