| 2008 |
|---|
| 37 | EE | Debarun Bhattacharjya,
Ross D. Shachter:
Sensitivity analysis in decision circuits.
UAI 2008: 34-42 |
| 2005 |
|---|
| 36 | EE | George C. Scott,
Ross D. Shachter:
Individualizing generic decision models using assessments as evidence.
Journal of Biomedical Informatics 38(4): 281-297 (2005) |
| 2004 |
|---|
| 35 | | Elizabeth S. Burnside,
Daniel L. Rubin,
Ross D. Shachter:
Improving a Bayesian network's ability to predict the probability of malignancy of microcalcifications on mammography.
CARS 2004: 1021-1026 |
| 2001 |
|---|
| 34 | EE | Daniel G. Shapiro,
Pat Langley,
Ross D. Shachter:
Using background knowledge to speed reinforcement learning in physical agents.
Agents 2001: 254-261 |
| 1999 |
|---|
| 33 | EE | Ross D. Shachter:
Efficient Value of Information Computation.
UAI 1999: 594-601 |
| 1998 |
|---|
| 32 | EE | Mark A. Peot,
Ross D. Shachter:
Learning From What You Don't Observe.
UAI 1998: 439-446 |
| 31 | EE | Ross D. Shachter:
Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams).
UAI 1998: 480-487 |
| 1996 |
|---|
| 30 | EE | Ross D. Shachter,
Marvin Mandelbaum:
A Measure of Decision Flexibility.
UAI 1996: 485-491 |
| 1995 |
|---|
| 29 | EE | David Heckerman,
Ross D. Shachter:
A Definition and Graphical Representation for Causality.
UAI 1995: 262-273 |
| 28 | EE | Tom Chávez,
Ross D. Shachter:
Decision Flexibility.
UAI 1995: 77-86 |
| 27 | | David Heckerman,
Ross D. Shachter:
Decision-Theoretic Foundations for Causal Reasoning.
J. Artif. Intell. Res. (JAIR) 3: 405-430 (1995) |
| 1994 |
|---|
| 26 | EE | Adriano Azevedo-Filho,
Ross D. Shachter:
Laplace's Method Approximations for Probabilistic Inference in Belief Networks with Continuous Variables.
UAI 1994: 28-36 |
| 25 | EE | David Heckerman,
Ross D. Shachter:
A Decision-based View of Causality.
UAI 1994: 302-310 |
| 24 | EE | William B. Poland,
Ross D. Shachter:
Three Approaches to Probability Model Selection.
UAI 1994: 478-483 |
| 23 | EE | Ross D. Shachter,
Stig K. Andersen,
Peter Szolovits:
Global Conditioning for Probabilistic Inference in Belief Networks.
UAI 1994: 514-522 |
| 1993 |
|---|
| 22 | EE | William B. Poland,
Ross D. Shachter:
Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties.
UAI 1993: 183-190 |
| 21 | EE | Ross D. Shachter,
Pierre Ndilikilikesha:
Using Potential Influence Diagrams for Probabilistic Inference and Decision Making.
UAI 1993: 383-390 |
| 20 | EE | Harold P. Lehmann,
Ross D. Shachter:
End-User Construction of Influence Diagrams for Bayesian Statistics.
UAI 1993: 48-54 |
| 1992 |
|---|
| 19 | EE | Brian Y. Chan,
Ross D. Shachter:
Structural Controllability and Observability in Influence Diagrams.
UAI 1992: 25-32 |
| 18 | EE | Ross D. Shachter,
Mark A. Peot:
Decision Making Using Probabilistic Inference Methods.
UAI 1992: 276-283 |
| 1991 |
|---|
| 17 | EE | Ross D. Shachter:
A Graph-Based Inference Method for Conditional Independence.
UAI 1991: 353-360 |
| 16 | | Mark A. Peot,
Ross D. Shachter:
Fusion and Propagation with Multiple Observations in Belief Networks.
Artif. Intell. 48(3): 299-318 (1991) |
| 1990 |
|---|
| 15 | | Ross D. Shachter,
Tod S. Levitt,
Laveen N. Kanal,
John F. Lemmer:
UAI '88: Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
North-Holland 1990 |
| 14 | | Max Henrion,
Ross D. Shachter,
Laveen N. Kanal,
John F. Lemmer:
UAI '89: Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
North-Holland 1990 |
| 13 | | Ross D. Shachter,
Bruce D'Ambrosio,
Brendan Del Favero:
Symbolic Probabilistic Inference in Belief Networks.
AAAI 1990: 126-131 |
| 12 | EE | Ross D. Shachter,
Stig K. Andersen,
Kim-Leng Poh:
Directed reduction algorithms and decomposable graphs.
UAI 1990: 197-208 |
| 1989 |
|---|
| 11 | EE | Ross D. Shachter:
Evidence Absorption and Propagation through Evidence Reversals.
UAI 1989: 173-190 |
| 10 | EE | Ross D. Shachter,
Mark A. Peot:
Simulation Approaches to General Probabilistic Inference on Belief Networks.
UAI 1989: 221-234 |
| 1988 |
|---|
| 9 | EE | Ross D. Shachter:
A linear approximation method for probabilistic inference.
UAI 1988: 93-104 |
| 8 | | Ross D. Shachter,
David M. Eddy,
Vic Hasselblad,
Robert Wolpert:
A heuristic Bayesian approach to knowledge acquisition: Application to analysis of tissue-type plasminogen activator.
Int. J. Approx. Reasoning 2(3): 342 (1988) |
| 7 | | Ross D. Shachter:
Efficient inference on generalized fault diagrams.
Int. J. Approx. Reasoning 2(3): 342 (1988) |
| 1987 |
|---|
| 6 | EE | Ross D. Shachter,
David M. Eddy,
Vic Hasselblad,
Robert Wolpert:
A Heuristic Bayesian Approach to Knowledge Acquisition: Application to the Analysis of Tissue-Type Plasminogen Activator.
UAI 1987: 183-190 |
| 5 | EE | Ross D. Shachter,
Leonard J. Bertrand:
Efficient Inference on Generalized Fault Diagrams.
UAI 1987: 325-332 |
| 4 | | Ross D. Shachter,
David Heckerman:
Thinking Backward for Knowledge Acquisition.
AI Magazine 8(3): 55-61 (1987) |
| 1986 |
|---|
| 3 | EE | Ross D. Shachter:
DAVID: influence diagram processing system for the macintosh.
UAI 1986: 191-196 |
| 2 | EE | Ross D. Shachter,
David Heckerman:
A backwards view for assessment.
UAI 1986: 317-324 |
| 1985 |
|---|
| 1 | EE | Ross D. Shachter:
Intelligent Probabilistic Inference.
UAI 1985: 371-382 |
