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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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ICML
2010
IEEE
14 years 11 months ago
Finite-Sample Analysis of LSTD
In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-differe...
Alessandro Lazaric, Mohammad Ghavamzadeh, Ré...
ECML
2006
Springer
15 years 1 months ago
Fisher Kernels for Relational Data
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Uwe Dick, Kristian Kersting
ICMLA
2004
14 years 11 months ago
LASSO: a learning architecture for semantic web ontologies
Expressing web page content in a way that computers can understand is the key to a semantic web. Generating ontological information from the web automatically using machine learni...
Christopher N. Hammack, Stephen D. Scott
ALT
2009
Springer
15 years 6 months ago
Approximation Algorithms for Tensor Clustering
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Stefanie Jegelka, Suvrit Sra, Arindam Banerjee
ICML
2009
IEEE
15 years 10 months ago
Nonparametric factor analysis with beta process priors
We propose a nonparametric extension to the factor analysis problem using a beta process prior. This beta process factor analysis (BPFA) model allows for a dataset to be decompose...
John William Paisley, Lawrence Carin