2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2013
Pushing Stochastic Gradient towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities
Tommi Vatanen, Tapani Raiko, Harri Valpola +1
Recently, we proposed to 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 co…
cs.MS2012★ 2 cited
Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework
Markus Harva, Tapani Raiko, Antti Honkela +2
A software library for constructing and learning probabilistic models is presented. The library offers a set of building blocks from which a large variety of static and dynamic mod…
cs.AI2012★ 2 cited
'Say EM' for Selecting Probabilistic Models for Logical Sequences
Kristian Kersting, Tapani Raiko
Many real world sequences such as protein secondary structures or shell logs exhibit a rich internal structures. Traditional probabilistic models of sequences, however, consider se…