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114
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ICML
2010
IEEE
15 years 3 months ago
Learning Deep Boltzmann Machines using Adaptive MCMC
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...
Ruslan Salakhutdinov
101
Voted
AUTOMATICA
2007
142views more  AUTOMATICA 2007»
15 years 2 months ago
Supervisory control using a new control-relevant switching
This paper presents a new supervisory control scheme, which is based on a control-relevant switching logic. Unlike most of the existing switching methods considering only estimato...
Tae-Woong Yoon, Jung-Su Kim, A. Stephen Morse
107
Voted
CORR
2010
Springer
69views Education» more  CORR 2010»
15 years 2 months ago
A Geometric View of Conjugate Priors
In Bayesian machine learning, conjugate priors are popular, mostly due to mathematical convenience. In this paper, we show that there are deeper reasons for choosing a conjugate pr...
Arvind Agarwal, Hal Daumé III
104
Voted
IJON
2006
51views more  IJON 2006»
15 years 2 months ago
Predicting synchronized neural assemblies from experimentally estimated phase-resetting curves
Neural-network dynamics frequently organize in assemblies of synchronized neurons that are thought to encode and store sensory information. We have investigated the mechanisms lea...
Roberto Fdez. Galán, Bard Ermentrout, Natha...
CORR
2007
Springer
100views Education» more  CORR 2007»
15 years 2 months ago
Finite Volume Analysis of Nonlinear Thermo-mechanical Dynamics of Shape Memory Alloys
In this paper, the finite volume method is developed to analyze coupled dynamic problems of nonlinear thermoelasticity. The major focus is given to the description of martensitic ...
Linxiang X. Wang, Roderick V. N. Melnik