INFOCOM
2011
IEEE
13 years 4 months ago
2011
IEEE
—In this paper, we propose a Bayesian-inference based recommendation system for online social networks. In our system, users share their content ratings with friends. The rating ...
ASMTA
2011
Springer
13 years 4 months ago
2011
Springer
Queueing delays experienced by packets buffered at a node are among the most difficult to predict when considering the performance of a flow in a network. The arrivals of packets a...
MMM
2011
Springer
13 years 4 months ago
2011
Springer
Probabilistic Latent Semantic Analysis (PLSA) has become a popular topic model for image clustering. However, the traditional PLSA method considers each image (document) independen...
JMLR
2010
13 years 11 months ago
2010
The problem is sequence prediction in the following setting. A sequence x1, . . . , xn, . . . of discrete-valued observations is generated according to some unknown probabilistic ...
NN
2000
Springer
14 years 15 days ago
2000
Springer
While sophisticated neural networks and graphical models have been developed for predicting conditional probabilities in a non-stationary environment, major improvements in the tr...
JAPLL
2007
14 years 19 days ago
2007
I’ll describe a range of systems for nonmonotonic conditionals that behave like conditional probabilities above a threshold. The rules that govern each system are probabilistical...
IJCAI
1989
14 years 1 months ago
1989
Nilsson's Probabilistic Logic is a set theoretic mechanism for reasoning with uncertainty. We propose a new way of looking at the probability constraints enforced by the fram...
FLAIRS
1998
14 years 2 months ago
1998
In this paper wesuggest a wayof using the rules of System P to propagate lower bounds on conditional probabilities. Usinga knowledgebase of default rules whichart, consideredto be...
UAI
2004
14 years 2 months ago
2004
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
UAI
2004
14 years 2 months ago
2004
Within the task of collaborative filtering two challenges for computing conditional probabilities exist. First, the amount of training data available is typically sparse with resp...