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APIN
1999
107views more  APIN 1999»
14 years 9 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
PG
2003
IEEE
15 years 2 months ago
Machine Learning for Computer Graphics: A Manifesto and Tutorial
I argue that computer graphics can benefit from a deeper use of machine learning techniques. I give an overview of what learning has to offer the graphics community, with an emph...
Aaron Hertzmann
PRL
2008
93views more  PRL 2008»
14 years 9 months ago
Learning to learn: From smart machines to intelligent machines
Since its birth, more than five decades ago, one of the biggest challenges of artificial intelligence remained the building of intelligent machines. Despite amazing advancements, ...
Bogdan Raducanu, Jordi Vitrià
84
Voted
AI
2007
Springer
14 years 9 months ago
Argument based machine learning
We present a novel approach to machine learning, called ABML (argumentation based ML). This approach combines machine learning from examples with concepts from the field of argum...
Martin Mozina, Jure Zabkar, Ivan Bratko
ICML
2009
IEEE
15 years 10 months ago
Learning to segment from a few well-selected training images
Alireza Farhangfar, Csaba Szepesvári, Russe...