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TRANSCI
2010
128views more  TRANSCI 2010»
13 years 3 months ago
An Information-Theoretic Sensor Location Model for Traffic Origin-Destination Demand Estimation Applications
To design a transportation sensor network, the decision-maker needs to determine what sensor investments should be made, as well as when, how, where and with what technologies. Th...
Xuesong Zhou, George F. List
NIPS
2007
13 years 6 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
JMLR
2008
209views more  JMLR 2008»
13 years 5 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
WWW
2009
ACM
14 years 6 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel
WSDM
2012
ACM
254views Data Mining» more  WSDM 2012»
12 years 26 days ago
Maximizing product adoption in social networks
One of the key objectives of viral marketing is to identify a small set of users in a social network, who when convinced to adopt a product will influence others in the network l...
Smriti Bhagat, Amit Goyal 0002, Laks V. S. Lakshma...