نتایج جستجو برای: gibbs sampling

تعداد نتایج: 219418  

2010
Guillaume Desjardins Aaron C. Courville Yoshua Bengio Pascal Vincent Olivier Delalleau

Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Networks. However, we find that it often does a very poor job of rendering the diversity of modes captured by the trained model. We suspect that this hinders the advantage that could in principle be brought by training alg...

2010
Guillaume Desjardins Aaron Courville Yoshua Bengio Pascal Vincent Olivier Delalleau

Alternating Gibbs sampling between visible and latent units is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Networks (DBN). However, we find that it often does a very poor job of rendering the diversity of modes captured by the trained model. We suspect that this property hinders RBM training met...

Journal: :CoRR 2014
Guillaume Desjardins Heng Luo Aaron C. Courville Yoshua Bengio

Restricted Boltzmann Machines (RBMs) are one of the fundamental building blocks of deep learning. Approximate maximum likelihood training of RBMs typically necessitates sampling from these models. In many training scenarios, computationally efficient Gibbs sampling procedures are crippled by poor mixing. In this work we propose a novel method of sampling from Boltzmann machines that demonstrate...

2011
Joseph Gonzalez Yucheng Low Arthur Gretton Carlos Guestrin

We explore the task of constructing a parallel Gibbs sampler, to both improve mixing and the exploration of high likelihood states. Recent work in parallel Gibbs sampling has focused on update schedules which do not guarantee convergence to the intended stationary distribution. In this work, we propose two methods to construct parallel Gibbs samplers guaranteed to draw from the targeted distrib...

Journal: :Proceedings of the National Academy of Sciences 2016

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