225 citations · 509 across the 11 of their papers we have counts for
12 papers · 1 filter
Probability Distributions Over Possible Worlds
Fahiem Bacchus
In Probabilistic Logic Nilsson uses the device of a probability distribution over a set of possible worlds to assign probabilities to the sentences of a logical language. In his pa…
Lp : A Logic for Statistical Information
Fahiem Bacchus
This extended abstract presents a logic, called Lp, that is capable of representing and reasoning with a wide variety of both qualitative and quantitative statistical information.…
Using Causal Information and Local Measures to Learn Bayesian Networks
Wai Lam, Fahiem Bacchus
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL p…
Using First-Order Probability Logic for the Construction of Bayesian Networks
Fahiem Bacchus
We present a mechanism for constructing graphical models, specifically Bayesian networks, from a knowledge base of general probabilistic information. The unique feature of our appr…
Using New Data to Refine a Bayesian Network
Wai Lam, Fahiem Bacchus
We explore the issue of refining an existent Bayesian network structure using new data which might mention only a subset of the variables. Most previous works have only considered…
Generating New Beliefs From Old
Fahiem Bacchus, Adam J. Grove, Joseph Y. Halpern +1
In previous work [BGHK92, BGHK93], we have studied the random-worlds approach -- a particular (and quite powerful) method for generating degrees of belief (i.e., subjective probabi…