UAI
2008
14 years 1 months ago
2008
We conjecture that the worst case number of experiments necessary and sufficient to discover a causal graph uniquely given its observational Markov equivalence class can be specif...
UAI
2008
14 years 1 months ago
2008
We address the problem of computing approximate marginals in Gaussian probabilistic models by using mean field and fractional Bethe approximations. As an extension of Welling and ...
UAI
2008
14 years 1 months ago
2008
Latent topic models have been successfully applied as an unsupervised topic discovery technique in large document collections. With the proliferation of hypertext document collect...
UAI
2008
14 years 1 months ago
2008
Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixedpo...
UAI
2008
14 years 1 months ago
2008
An efficient policy search algorithm should estimate the local gradient of the objective function, with respect to the policy parameters, from as few trials as possible. Whereas m...
UAI
2008
14 years 1 months ago
2008
A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown p...
UAI
2008
14 years 1 months ago
2008
Although fully generative models have been successfully used to model the contents of text documents, they are often awkward to apply to combinations of text data and document met...
UAI
2008
14 years 1 months ago
2008
When the initial and transition probabilities of a finite Markov chain in discrete time are not well known, we should perform a sensitivity analysis. This is done by considering a...
UAI
2008
14 years 1 months ago
2008
This paper describes a new algorithm to solve the decision making problem in Influence Diagrams based on algorithms for credal networks. Decision nodes are associated to imprecise...
UAI
2008
14 years 1 months ago
2008
We consider how an agent should update her uncertainty when it is represented by a set P of probability distributions and the agent observes that a random variable X takes on valu...