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ICML
1999
IEEE
16 years 5 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
ALT
2008
Springer
16 years 1 months ago
Optimally Learning Social Networks with Activations and Suppressions
In this paper we consider the problem of learning hidden independent cascade social networks using exact value injection queries. These queries involve activating and suppressing a...
Dana Angluin, James Aspnes, Lev Reyzin
CIKM
2009
Springer
15 years 11 months ago
Large margin transductive transfer learning
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
Brian Quanz, Jun Huan
COLT
2007
Springer
15 years 10 months ago
Property Testing: A Learning Theory Perspective
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
Dana Ron
ICML
2004
IEEE
15 years 10 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul