225 citations · 349 across the 10 of their papers we have counts for
10 papers
Logarithmic-Time Updates and Queries in Probabilistic Networks
Arthur L. Delcher, Adam J. Grove, Simon Kasif +1
In this paper we propose a dynamic data structure that supports efficient algorithms for updating and querying singly connected Bayesian networks (causal trees and polytrees). In t…
Probability Estimation in Face of Irrelevant Information
Adam J. Grove, Daphne Koller
In this paper, we consider one aspect of the problem of applying decision theory to the design of agents that learn how to make decisions under uncertainty. This aspect concerns ho…
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…
Graphical Models for Preference and Utility
Fahiem Bacchus, Adam J. Grove
Probabilistic independence can dramatically simplify the task of eliciting, representing, and computing with probabilities in large domains. A key technique in achieving these bene…
Probability Update: Conditioning vs. Cross-Entropy
Adam J. Grove, Joseph Y. Halpern
Conditioning is the generally agreed-upon method for updating probability distributions when one learns that an event is certainly true. But it has been argued that we need other r…
Learning Bayesian Nets that Perform Well
Russell Greiner, Adam J. Grove, Dale Schuurmans
A Bayesian net (BN) is more than a succinct way to encode a probabilistic distribution; it also corresponds to a function used to answer queries. A BN can therefore be evaluated by…