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JMLR
2012
13 years 9 months ago
A General Framework for Structured Sparsity via Proximal Optimization
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...
JMLR
2012
13 years 9 months ago
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
Avneesh Singh Saluja, Priya Krishnan Sundararajan,...
JMLR
2012
13 years 9 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
JMLR
2012
13 years 9 months ago
Randomized Optimum Models for Structured Prediction
One approach to modeling structured discrete data is to describe the probability of states via an energy function and Gibbs distribution. A recurring difficulty in these models is...
Daniel Tarlow, Ryan Prescott Adams, Richard S. Zem...
JMLR
2012
13 years 9 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
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