INFOCOM
2011
IEEE
12 years 8 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
12 years 8 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
12 years 8 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 3 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
13 years 4 months 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
13 years 4 months 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
13 years 6 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
13 years 6 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
13 years 6 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
13 years 6 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...