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ILP
1999
Springer
15 years 10 months ago
Probabilistic Relational Models
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Daphne Koller
KDD
1998
ACM
120views Data Mining» more  KDD 1998»
15 years 10 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen
JMLR
2012
13 years 9 months ago
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....
ISVC
2009
Springer
16 years 1 months ago
Weight, Sex, and Facial Expressions: On the Manipulation of Attributes in Generative 3D Face Models
Generative 3D Face Models are expressive models with applications in modelling and editing. They are learned from example faces, and offer a compact representation of the continuou...
Brian Amberg, Pascal Paysan, Thomas Vetter
GECCO
2009
Springer
101views Optimization» more  GECCO 2009»
16 years 1 months ago
Modeling UCS as a mixture of experts
We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...