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IWANN
2007
Springer
16 years 26 days ago
Non-parametric Residual Variance Estimation in Supervised Learning
The residual variance estimation problem is well-known in statistics and machine learning with many applications for example in the field of nonlinear modelling. In this paper, we...
Elia Liitiäinen, Amaury Lendasse, Francesco C...
ICML
2009
IEEE
16 years 7 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
ICML
2004
IEEE
16 years 7 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
ICALT
2003
IEEE
16 years 13 hour ago
Gaining Computational Literacy by Creating Hybrid Aesthetic Learning Spaces
Although the technical skills of pupils are quite high, the current approach to gain media literacy still focusses on updating software applying skills, rather than exploring the ...
Daniela Reimann, Michael Herczeg, Thomas Winkler, ...
COLT
1992
Springer
15 years 10 months ago
Language Learning from Stochastic Input
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Shyam Kapur, Gianfranco Bilardi