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JMLR
2008
230views more  JMLR 2008»
13 years 7 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
ICANN
1997
Springer
13 years 11 months ago
On Learning Soccer Strategies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...
ECAI
2006
Springer
13 years 11 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani
ETS
2000
IEEE
155views Hardware» more  ETS 2000»
13 years 7 months ago
Using technologies in teaching: an initiative in academic staff development
Academic staff development in the pedagogical applications of new technologies is fundamental to the transformation of teaching and learning in tertiary education settings. We pre...
Christine Spratt, Stuart Palmer, Jo Coldwell
WWW
2009
ACM
14 years 8 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel