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ML
2012
ACM
385views Machine Learning» more  ML 2012»
13 years 10 months ago
An alternative view of variational Bayes and asymptotic approximations of free energy
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Kazuho Watanabe
DAC
2012
ACM
13 years 4 months ago
ComPLx: A Competitive Primal-dual Lagrange Optimization for Global Placement
We develop a projected-subgradient primal-dual Lagrange optimization for global placement, that can be instantiated with a variety of interconnect models. It decomposes the origin...
Myung-Chul Kim, Igor L. Markov
PEWASUN
2008
ACM
15 years 3 months ago
Communication models for throughput optimization in mesh networks
There has been extensive research focused on maximizing the throughput of wireless networks in general and mesh networks in particular. Recently, techniques have been developed th...
Stephan Bohacek, Peng Wang
125
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GLVLSI
2008
IEEE
183views VLSI» more  GLVLSI 2008»
15 years 3 months ago
An analytical model for the upper bound on temperature differences on a chip
The main contribution of this work is an analytical model for finding the upper bound on the temperature difference among various locations on the die. The proposed model can be u...
Shervin Sharifi, Tajana Simunic Rosing
UAI
2004
15 years 3 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani