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JMLR
2010
96views more  JMLR 2010»
13 years 5 months ago
Posterior Regularization for Structured Latent Variable Models
Kuzman Ganchev, João Graça, Jennifer...
JMLR
2010
61views more  JMLR 2010»
13 years 5 months ago
Model-based Boosting 2.0
This is an extended version of the manuscript Torsten Hothorn, Peter B
Torsten Hothorn, Peter Bühlmann, Thomas Kneib...
JMLR
2010
154views more  JMLR 2010»
13 years 5 months ago
MOA: Massive Online Analysis
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernha...
JMLR
2010
136views more  JMLR 2010»
13 years 5 months ago
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti...
JMLR
2010
152views more  JMLR 2010»
13 years 5 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
JMLR
2010
124views more  JMLR 2010»
13 years 5 months ago
Consistent Nonparametric Tests of Independence
Three simple and explicit procedures for testing the independence of two multi-dimensional random variables are described. Two of the associated test statistics (L1, log-likelihoo...
Arthur Gretton, László Györfi
JMLR
2010
161views more  JMLR 2010»
13 years 5 months ago
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM
Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space, but training and testing large data sets is ...
Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Micha...
JMLR
2010
125views more  JMLR 2010»
13 years 5 months ago
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Miki Aoyagi
JMLR
2010
140views more  JMLR 2010»
13 years 5 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
JMLR
2010
185views more  JMLR 2010»
13 years 5 months ago
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
Franz Pernkopf, Jeff A. Bilmes