831 citations · 4.5k across the 36 of their papers we have counts for
36 papers
Plausibility Measures: A User's Guide
Nir Friedman, Joseph Y. Halpern
We examine a new approach to modeling uncertainty based on plausibility measures, where a plausibility measure just associates with an event its plausibility, an element is some pa…
On the Sample Complexity of Learning Bayesian Networks
Nir Friedman, Zohar Yakhini
In recent years there has been an increasing interest in learning Bayesian networks from data. One of the most effective methods for learning such networks is based on the minimum…
A Qualitative Markov Assumption and its Implications for Belief Change
Nir Friedman, Joseph Y. Halpern
The study of belief change has been an active area in philosophy and AI. In recent years two special cases of belief change, belief revision and belief update, have been studied in…
Learning Bayesian Networks with Local Structure
Nir Friedman, Moises Goldszmidt
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly r…
Context-Specific Independence in Bayesian Networks
Craig Boutilier, Nir Friedman, Moises Goldszmidt +1
Bayesian networks provide a language for qualitatively representing the conditional independence properties of a distribution. This allows a natural and compact representation of t…
Image Segmentation in Video Sequences: A Probabilistic Approach
Nir Friedman, Stuart Russell
"Background subtraction" is an old technique for finding moving objects in a video sequence for example, cars driving on a freeway. The idea is that subtracting the current image f…