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JMLR
2007
137views more  JMLR 2007»
15 years 6 months ago
Building Blocks for Variational Bayesian Learning of Latent Variable Models
We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, a...
Tapani Raiko, Harri Valpola, Markus Harva, Juha Ka...
ML
2000
ACM
126views Machine Learning» more  ML 2000»
15 years 6 months ago
Learning to Play Chess Using Temporal Differences
In this paper we present TDLEAF( ), a variation on the TD( ) algorithm that enables it to be used in conjunction with game-tree search. We present some experiments in which our che...
Jonathan Baxter, Andrew Tridgell, Lex Weaver
RAS
2000
161views more  RAS 2000»
15 years 6 months ago
Active object recognition by view integration and reinforcement learning
A mobile agent with the task to classify its sensor pattern has to cope with ambiguous information. Active recognition of three-dimensional objects involves the observer in a sear...
Lucas Paletta, Axel Pinz
ARTMED
1999
92views more  ARTMED 1999»
15 years 6 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....
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
15 years 5 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas