most citedEmpirical Analysis of Predictive Algorithms for Collaborative Filtering

4.5k citations · 5.6k across the 19 of their papers we have counts for

collaborators

19 papers

cs.AI201348 cited

Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (1993)

David Heckerman, E. Mamdani

This is the Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence, which was held in Washington, DC, July 9-11, 1993

cs.AI201370 cited

Probabilistic Interpretations for MYCIN's Certainty Factors

David Heckerman

This paper examines the quantities used by MYCIN to reason with uncertainty, called certainty factors. It is shown that the original definition of certainty factors is inconsistent…

cs.AI2013

A Backwards View for Assessment

Ross D. Shachter, David Heckerman

Much artificial intelligence research focuses on the problem of deducing the validity of unobservable propositions or hypotheses from observable evidence.! Many of the knowledge re…

cs.AI2013

An Axiomatic Framework for Belief Updates

David Heckerman

In the 1940's, a physicist named Cox provided the first formal justification for the axioms of probability based on the subjective or Bayesian interpretation. He showed that if a m…

cs.AI20133 cited

The Myth of Modularity in Rule-Based Systems

David Heckerman, Eric J. Horvitz

In this paper, we examine the concept of modularity, an often cited advantage of the ruled-based representation methodology. We argue that the notion of modularity consists of two…

cs.AI2013

The Role of Calculi in Uncertain Inference Systems

Michael P. Wellman, David Heckerman

Much of the controversy about methods for automated decision making has focused on specific calculi for combining beliefs or propagating uncertainty. We broaden the debate by (1) e…