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AROBOTS
2010
194views more  AROBOTS 2010»
14 years 8 months ago
Computationally efficient solutions for tracking people with a mobile robot: an experimental evaluation of Bayesian filters
Abstract Modern service robots will soon become an essential part of modern society. As they have to move and act in human environments, it is essential for them to be provided wit...
Nicola Bellotto, Huosheng Hu
CSDA
2011
14 years 5 months ago
Approximate forward-backward algorithm for a switching linear Gaussian model
Motivated by the application of seismic inversion in the petroleum industry we consider a hidden Markov model with two hidden layers. The bottom layer is a Markov chain and given ...
Hugo Hammer, Håkon Tjelmeland
JMLR
2010
140views more  JMLR 2010»
14 years 4 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
CHES
2011
Springer
254views Cryptology» more  CHES 2011»
13 years 10 months ago
Extractors against Side-Channel Attacks: Weak or Strong?
Randomness extractors are important tools in cryptography. Their goal is to compress a high-entropy source into a more uniform output. Beyond their theoretical interest, they have ...
Marcel Medwed, François-Xavier Standaert
CORR
2012
Springer
183views Education» more  CORR 2012»
13 years 5 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar