Sciweavers

CVPR
2012
IEEE
12 years 1 months ago
The Shape Boltzmann Machine: A strong model of object shape
A good model of object shape is essential in applications such as segmentation, object detection, inpainting and graphics. For example, when performing segmentation, local constra...
S. M. Ali Eslami, Nicolas Heess, John M. Winn
CVPR
2012
IEEE
12 years 1 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
JMLR
2012
12 years 1 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
JMLR
2012
12 years 1 months ago
Multiple Texture Boltzmann Machines
We assess the generative power of the mPoTmodel of [10] with tiled-convolutional weight sharing as a model for visual textures by specifically training on this task, evaluating m...
Jyri J. Kivinen, Christopher K. I. Williams
AAAI
2011
12 years 11 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal
NPL
1998
133views more  NPL 1998»
13 years 11 months ago
Parallel Coarse Grain Computing of Boltzmann Machines
Abstract. The resolution of combinatorial optimization problems can greatly benefit from the parallel and distributed processing which is characteristic of neural network paradigm...
Julio Ortega, Ignacio Rojas, Antonio F. Día...
APIN
1999
107views more  APIN 1999»
13 years 11 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
NIPS
2008
14 years 26 days ago
Implicit Mixtures of Restricted Boltzmann Machines
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
Vinod Nair, Geoffrey E. Hinton