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CN
2010
145views more  CN 2010»
13 years 5 months ago
Network virtualization in energy-efficient office environments
The rising costs of energy and world-wide desire to reduce CO2 emissions has led to an increased concern over the energy efficiency of information and communication technology. Wh...
Andreas Berl, Nicholas J. P. Race, Johnathan Ishma...
JMLR
2010
202views more  JMLR 2010»
13 years 3 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
JMLR
2010
149views more  JMLR 2010»
13 years 3 months ago
Coherent Inference on Optimal Play in Game Trees
Round-based games are an instance of discrete planning problems. Some of the best contemporary game tree search algorithms use random roll-outs as data. Relying on a good policy, ...
Philipp Hennig, David H. Stern, Thore Graepel
TIP
2010
164views more  TIP 2010»
13 years 3 months ago
A Marked Point Process for Modeling Lidar Waveforms
Lidar waveforms are 1D signals representing a train of echoes caused by reflections at different targets. Modeling these echoes with the appropriate parametric function is useful ...
Clément Mallet, Florent Lafarge, Michel Rou...
ESOP
2011
Springer
13 years 10 days ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...