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NECO
2010
136views more  NECO 2010»
13 years 6 months ago
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines
To allow the hidden units of a restricted Boltzmann machine to model the transformation between two successive images, Memisevic and Hinton (2007) introduced three-way multiplicat...
Roland Memisevic, Geoffrey E. Hinton
FLAIRS
1998
13 years 9 months ago
Lazy Transformation-Based Learning
Weintroduce a significant improvementfor a relatively newmachine learning methodcalled Transformation-Based Learning. By applying a MonteCarlo strategy to randomly sample from the...
Ken Samuel
BMVC
2010
13 years 5 months ago
Implicit Shape Kernel for Discriminative Learning of the Hough Transform Detector
The Hough transform provides an efficient way to detect objects. Various methods have been proposed to achieve discriminative learning of the Hough transform, but they have usuall...
Yimeng Zhang, Tsuhan Chen
JMLR
2012
11 years 10 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
ICPR
2008
IEEE
14 years 2 months ago
Learning a discriminative sparse tri-value transform
Simple binary patterns have been successfully used for extracting feature representations for visual object classification. In this paper, we present a method to learn a set of d...
Zhenhua Qu, Guoping Qiu, Pong Chi Yuen