Prakash P. Shenoy
Ronald G. Harper Distinguished Professor of Artificial Intelligence

Publications


REFEREED PUBLICATIONS IN JOURNALS AND EDITED BOOKS

  • Denœux, T. and P. P. Shenoy, "An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Functions," International Journal of Approximate Reasoning, Vol. 124, No. 9, 2020, 194--216. DOI PDF (607 KB)
  • Jiroušek, R. and P. P. Shenoy, "On Properties of a New Decomposable Entropy of Dempster-Shafer Belief Functions," International Journal of Approximate Reasoning, Vol. 119, No. 4, 2020, 260--279. DOI PDF (765 KB)
  • Tan, Y. and P. P. Shenoy, "A Bias-Variance Based Heuristic for Constructing a Hybrid Logistic Regression-Naïve Bayes Model for Classification," International Journal of Approximate Reasoning, Vol. 117, No. 2, 2020, pp. 15--28. DOI PDF (468 KB). A working paper that includes R code for implementing our algorithm is included in WP337 (538 KB).
  • Shenoy, P. P., "An Expectation Operator for Belief Functions in the Dempster-Shafer Theory," International Journal of General Systems, Vol. 49, No. 1, 2020, pp. 112--141. DOI PDF (460 KB).
  • Denœux, T. and P. P. Shenoy, "An Axiomatic Utility Theory for Dempster-Shafer Belief Functions," in J. de Bock, C. P. de Campos, G. de Cooman, E. Quaeghebeur, and G. Wheeler (eds.), Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, Proceedings of Machine Learning Research, Vol. 103, 2019, pp. 145--155. WWW PDF
  • Jaunzemis, A. D., M. J. Holzinger, M. W. Chan, and P. P. Shenoy, "Evidence Gathering for Hypothesis Resolution Using Judicial Evidential Reasoning," Information Fusion, Vol. 49, No. 9, 2019, pp. 26--45. DOI PDF
  • Singha, S. and P. P. Shenoy, "An Adaptive Heuristic for Feature Selection based on Complementarity," Machine Learning, Vol. 107, No. 12, 2018, pp. 2027--2071. DOI PDF (402KB)
  • Jiroušek, R. and P. P. Shenoy, "A Decomposable Entropy of Belief Functions in the Dempster-Shafer Theory" in S. Destercke, T. Denœux, F. Cuzzolin, and A. Martin (eds.), Belief Functions: Theory and Applications, 5th International Conference, BELIEF 2018, Lecture Notes in Artificial Intelligence, Vol. 11069, pp. 146--154, 2018, Springer Nature, Switzerland. DOI PDF (946KB)
  • Jiroušek, R. and P. P. Shenoy, "Combination and Composition in Probabilistic Models," in L. H. Ahn, L. S. Dong, V. Kreinovich, and N. N. Thach (eds.), Econometrics for Financial Applications: ECONVN 2018 Conference Proceedings, Studies in Computational Intelligence, Vol. 760, 2018, pp. 120--133, Springer, Cham. DOI PDF (172 KB)
  • Jiroušek, R. and P. P. Shenoy, "A New Definition of Entropy of Belief Functions in the Dempster-Shafer Theory," International Journal of Approximate Reasoning, Vol. 92, No. 1, January 2018, pp. 49--65. DOI PDF (709.1KB)
  • Cobb, B. R. and P. P. Shenoy, "Inference in Hybrid Bayesian Networks with Nonlinear Deterministic Conditionals," International Journal of Intelligent Systems, Vol. 32, No. 12, December 2017, pp. 1217--1246. DOI PDF (1.199MB)
  • Singha, S., S. Hillmer, and P. P. Shenoy, "On Computing Probabilities of Dismissal of 10b-5 Securities Class-Action Cases," Decision Support Systems, Vol. 94, No. 2, February 2017, pp. 29--41. DOI PDF (1.60 MB)
  • Cinicioglu, E. N. and P. P. Shenoy, "A New Heuristic for Learning Bayesian Networks from Limited Datasets: A Real-Time Recommendation System Application with RFID System in Grocery Stores," Annals of Operations Research, Vol. 244, No. 2, 2016, pp. 385--405. DOI PDF (823 KB)

  • Tan, Y., P. P. Shenoy, M. W. Chan, and P. M. Romberg, "On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification," in A. Antonucci, G. Corani, and C. P. de Campos (eds.), Proceedings of Machine Learning Research, Vol. 52: Conference on Probabilistic Graphical Models, 6-9 September 2016, Lugano, Switzerland, pp. 523--534. WWW PDF (197 KB)
  • Jiroušek, R. and P. P. Shenoy, "Entropy of Belief Functions in the Dempster-Shafer Theory: A New Perspective," in J. Vejnarová and V. Kratochvíl (eds.), Belief Functions: Theory and Applications, Lecture Notes in Artificial Intelligence, Vol. 9861, 2016, pp. 3-13, Springer International Publishing, Switzerland. DOI PDF (197 KB)
  • Jiroušek, R. and P. P. Shenoy, "Causal Compositional Models in Valuation-Based Systems with Examples in Specific Theories," International Journal of Approximate Reasoning, Vol. 72, No. 1, 2016, pp. 95--112. DOI PDF
  • Shenoy, P. P., R. Rumí and A. Salmerón, "Practical Aspects of Solving Hybrid Bayesian Networks Containing Deterministic Conditionals," International Journal of Intelligent Systems, Vol. 30, No. 3, 2015, pp. 265--291. DOI PDF
  • Jiroušek, R. and P. P. Shenoy, "Causal Compositional Models in Valuation-Based Systems," in F. Cuzzolin (ed.), Belief Functions: Theory and Applications, Lecture Notes in Computer Science, Vol. 8764, 2014, pp. 256--264, Springer International Publishing, Switzerland. DOI PDF (177 KB)

  • Jiroušek, R. and P. P. Shenoy, "Compositional Models in Valuation-Based Systems," International Journal of Approximate Reasoning, Vol. 55, No. 1, 2014, pp. 277--293. DOI PDF
  • Jiroušek, R. and P. P. Shenoy, "Conditioning in Decomposable Compositional Models in Valuation-Based Systems," in S. Greco, B. Bouchon-Meunier, G. Coletti, M. Fedrizzi, B. Matarazzo, and R. Yager (eds.), Advances in Computational Intelligence, Lecture Notes in Computer Science 300, Part IV, 2012, pp. 676--685, Springer-Verlag, Berlin. DOI PDF (165 KB)

  • Jiroušek, R. and P. P. Shenoy, "Compositional Models in Valuation-Based Systems," in T. Denoeux and M.-H. Masson (eds.), Belief Functions: Theory and Applications, Advances in Intelligent and Soft Computing, Vol. 164, 2012, pp. 221--228, Springer, Heidelberg. DOI PDF (124 KB)

  • Shenoy, P. P., "Two Issues in Using Mixtures of Polynomials for Inference in Hybrid Bayesian Networks," International Journal of Approximate Reasoning, Vol. 53, No. 5, 2012, pp. 847--866. DOI PDF (1.4 MB). A copy of this paper that includes Mathematica code for all results in the paper can be downloaded as WP No. 323 (10.2 MB).
  • Li, Y. and P. P. Shenoy, "A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions," Decision Analysis, Vol. 9, No. 1, March 2012, pp. 55--75. DOI PDF (1.7MB). A copy of this paper that includes Mathematica code for the solution of the two examples in the paper can be downloaded as WP No. 322 (8.1 MB).
  • Shenoy, P. P., "A Re-Definition of Mixtures of Polynomials for Inference in Hybrid Bayesian Networks," in W. Liu (ed.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty -- ECSQARU 2011, Lecture Notes in Artificial Intelligence, Vol. 6717, pp. 98--109, Springer, Heidelberg. DOI PDF (256 KB).
  • Shenoy, P. P. and J. C. West, "Extended Shenoy-Shafer Architecture for Inference in Hybrid Bayesian Networks with Deterministic Conditionals," International Journal of Approximate Reasoning, Vol. 52, No. 6, September 2011, pp. 805--818. DOI PDF (1 MB).
  • Shenoy, P. P. and J. C. West, "Inference in Hybrid Bayesian Networks Using Mixtures of Polynomials," International Journal of Approximate Reasoning, Vol. 52, No. 5, July 2011, pp. 641--657. DOI PDF (766 KB).
  • Giang, P. H. and P. P. Shenoy, "A Decision Theory for Partially Consonant Belief Functions," International Journal of Approximate Reasoning, Vol. 52, No. 3, 2011, pp. 375--394. DOI PDF (564 KB).
  • Bielza, C., M. Gomez, and P. P. Shenoy, "A Review of Representation Issues and Modeling Challenges with Influence Diagrams," Omega: International Journal of Management Science, Vol. 39, No. 3, 2011, pp. 227--241. DOI PDF (311 KB).
  • Bielza, C., M. Gomez, and P. P. Shenoy, "Modeling Challenges with Influence Diagrams: Constructing Probability and Utility Models," Decision Support Systems, Vol. 49, No. 4, 2010, pp. 354--364. DOI PDF (471 KB).
  • Li, Y. and P. P. Shenoy, "Solving Hybrid Influence Diagrams with Deterministic Variables," in P. Grunwald and P. Spirtes (eds.), Uncertainty in Artificial Intelligence, Vol. 26, 2010, pp. 322--331, AUAI Press, Corvallis, OR. PDF (1.33 MB).
  • Shenoy, P. P. and J. C. West, "Inference in Hybrid Bayesian Networks with Deterministic Variables," in C. Sossai and G. Chemello (eds.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty -- 10th ECSQARU, Lecture Notes in Artificial Intelligence, Vol. 5590, 2009, pp. 46--58, Springer-Verlag, Berlin. DOI PDF (224 KB)
  • Cinicioglu, E. N. and P. P. Shenoy, "Arc Reversals in Hybrid Bayesian Networks with Deterministic Variables," International Journal of Approximate Reasoning, Vol. 50, No. 5, 2009, pp. 763--777. DOI PDF (1.1 MB).
  • Cobb, B. R. and P. P. Shenoy, "Decision Making with Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials," European Journal of Operational Research, Vol. 186, No. 1, 2008, pp. 261--275. DOI PDF (216 KB).
  • Cinicioglu, E. N., C. Kocabasoglu, and P. P. Shenoy, "Use of Radio Frequency Identification for Targeted Advertising: A Collaborative Filtering Approach Using Bayesian Networks," in K. Mellouli (ed.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Lecture Notes in Artificial Intelligence, Vol. 4724, 2007, pp. 889--900, Springer-Verlag, Berlin. DOI PDF (248 KB)

  • Sun, L. and P. P. Shenoy, "Using Bayesian Networks for Bankruptcy Prediction: Some Methodological Issues," European Journal of Operational Research, Vol. 180, No. 2, 2007, pp. 738--753. DOI PDF (371 KB).
  • Shenoy, P. P., "Inference in Hybrid Bayesian Networks Using Mixtures of Gaussians," in R. Dechter and T. Richardson (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 22nd Conference, 2006, pp. 428--436, AUAI Press, Corvallis, OR. PDF (2.4 MB).
  • Liu, L., C. Shenoy, and P. P. Shenoy, "Knowledge Representation and Integration for Portfolio Evaluation Using Linear Belief Functions," IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, Vol. 36, No. 4, 2006, pp. 774--785. DOI PDF (5.2 MB).
  • Cobb, B. R., P. P. Shenoy, and R. Rumí "Approximating Probability Density Functions in Hybrid Bayesian Networks with Mixtures of Truncated Exponentials," Statistics and Computing, Vol. 16, No. 3, 2006, pp. 293--308. DOI PDF (441KB).
  • Jensen, F. V., T. D. Nielsen, and P. P. Shenoy. "Sequential Influence Diagrams: A Unified Asymmetry Framework," International Journal of Approximate Reasoning, Vol 42, Nos. 1-2, 2006, pp. 101--118. DOI PDF (306 KB).
  • Cobb, B. R. and P. P. Shenoy, "Operations for Inference in Continuous Bayesian Networks with Linear Deterministic Variables," International Journal of Approximate Reasoning, Vol 42, Nos. 1-2, 2006, pp. 21--36. DOI PDF (323 KB).
  • Cobb, B. R. and P. P. Shenoy, "On the Plausibility Transformation Method for Translating Belief Function Models to Probability Models," International Journal of Approximate Reasoning, Vol. 41, No. 3, 2006, pp. 314--340. DOI PDF (785KB). A longer working paper with more details and examples can be downloaded as Working Paper No. 293 (1440 KB)
  • Cobb, B. R. and P. P. Shenoy, "Inference in Hybrid Bayesian Networks with Mixtures of Truncated Exponentials," International Journal of Approximate Reasoning, Vol. 41, No. 3, 2006, pp. 257--286. DOI PDF (556 KB).
  • Demirer, R. and P. P. Shenoy, "Sequential Valuation Networks for Asymmetric Decision Problems," European Journal of Operational Research, Vol. 169, No. 1, 2006, pp. 286--309. DOI PDF (756 KB).
  • Cobb, B. R. and P. P. Shenoy, "Hybrid Bayesian Networks with Linear Deterministic Variables" in F. Bacchus and T. Jaakkola (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 21st Conference, 2005, pp. 136--144, AUAI Press, Corvallis, OR. PDF (492 KB).
  • Cobb, B. R. and P. P. Shenoy, "Nonlinear Deterministic Relationships in Bayesian Networks," in L. Godo (ed.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Lecture Notes in Artificial Intelligence, Vol. 3571, 2005, pp. 27--38, Springer-Verlag, Berlin. DOI PDF (170 KB).
  • Giang, P. H. and P. P. Shenoy, "Decision Making on the Sole Basis of Statistical Likelihood," Artificial Intelligence, Vol. 165, No. 2, 2005, pp. 137--163. DOI PDF (500 KB)
  • Giang, P. H. and P. P. Shenoy, "Two Axiomatic Approaches to Decision Making Using Possibility Theory," European Journal of Operational Research, Vol. 162, No. 2, 2005, pp. 450--467. DOI PDF (306 KB).
  • Nadkarni, S. and P. P. Shenoy, "A Causal Mapping Approach to Constructing Bayesian Networks," Decision Support Systems, Vol. 38, No. 2, 2004, pp. 259--281. DOI PDF (304 KB).
  • Cobb, B. R. and P. P. Shenoy, "Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials" in M. Chickering and J. Halpern (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 20th Conference, 2004, pp. 85--93, AUAI Press, Arlington, VA. PDF (273 KB).
  • Liu, L. and P. P. Shenoy, "Representing Asymmetric Decision Problems Using Coarse Valuations" Decision Support Systems, Vol. 37, No. 1, 2004, pp. 119--135. DOI PDF (274 KB).
  • Charnes, J. M. and P. P. Shenoy, "Multi-Stage Monte Carlo Method for Solving Influence Diagrams Using Local Computation," Management Science, Vol. 50, No. 3, 2004, pp. 405--418. DOI PDF (188 KB). An online appendix to the published version is also available at the same URL.
  • Cobb, B. R. and P. P. Shenoy, "A Comparison of Bayesian and Belief Function Reasoning," Information Systems Frontiers, Vol 5, No. 4, 2003, pp. 345--358. DOI PDF (404 KB).
  • Giang, P. H. and P. P. Shenoy, "Decision Making with Partially Consonant Belief Functions" in U. Kjaerulff and C. Meek (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 19th Conference, 2003, 272--280, Morgan Kaufmann, San Francisco, CA. PDF (256 KB).
  • Liu, L., C. Shenoy, and P. P. Shenoy, "A Linear Belief Function Approach to Portfolio Evaluation" in U. Kjaerulff and C. Meek (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 19th Conference, Vol. 19, 2003, 370--377, Morgan Kaufmann, San Francisco, CA. PDF (1687 KB).
  • Cobb, B. R. and P. P. Shenoy, "A Comparison of Methods for Transforming Belief Function Models to Probability Models," in T. D. Nielsen and N. L. Zhang (eds.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Lecture Notes in Artificial Intelligence, Vol. 2711, pp. 255--266, Springer-Verlag, 2003. DOI PDF (772 KB).
  • Giang, P. H. and P. P. Shenoy, "Statistical Decisions Using Likelihood Information Without Prior Probabilities" in A. Darwiche and N. Friedman (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 18th Conference, 2002, pp. 170--178, Morgan Kaufmann, San Francisco, CA. PDF (297 KB).
  • Shenoy, C. and P. P. Shenoy, "Modeling Financial Portfolios Using Belief Functions," in R. P. Srivastava and T. J. Mock (eds.), Belief Functions in Business Decisions, Studies in Fuzziness and Soft Computing, Vol. 88, 2002, pp. 316--332, Physica-Verlag, Heidelberg. DOI PDF (153 KB).
  • Demirer, R. and P. P. Shenoy, "Sequential Valuation Networks: A New Graphical Technique for Asymmetric Decision Problems," in S. Benferhat and P. Besnard (eds.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Lecture Notes in Artificial Intelligence, Vol. 2143, 2001, pp. 252--265, Springer-Verlag, Heidelberg. DOI PDF (143 KB).
  • Giang, P. H. and P. P. Shenoy, "A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory" in J. Breese and D. Koller (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 17th Conference, 2001, pp. 162--170, Morgan Kaufmann, San Francisco, CA. PDF (312 KB).
  • Nadkarni, S. and P. P. Shenoy, "A Bayesian Network Approach to Making Inferences in Causal Maps," European Journal of Operational Research, Vol. 128, No. 3, 2001, pp. 479--498. DOI PDF (344 KB).
  • Kohlas, J. and P. P. Shenoy, "Computation in Valuation Algebras," in D. Gabbay and P. Smets (eds.), Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 5: Algorithms for Uncertainty and Defeasible Reasoning, 2000, pp. 5--39, Kluwer Academic Publishers, Dordrecht. DOI PDF (309 KB).
  • Giang, P. H. and P. P. Shenoy, "A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs" in C. Boutilier and M. Goldszmidt (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 16th Conference, 2000, pp. 220--229, Morgan Kaufmann, San Francisco, CA. PDF (245 KB).
  • Shenoy, P. P., "Valuation Network Representation and Solution of Asymmetric Decision Problems," European Journal of Operational Research, Vol. 121, No. 3, 2000, pp. 579--608. DOI PDF (472 KB).
  • Shenoy, C. and P. P. Shenoy, "Bayesian Network Models of Portfolio Risk and Return," in Y. S. Abu-Mostafa, B. LeBaron, A. W. Lo, and A. S. Weigend (eds.), Computational Finance 1999, 2000, 87--106, MIT Press, Cambridge, MA. WWW PDF (155 KB).
  • Bielza, C. and P. P. Shenoy, "A Comparison of Graphical Techniques for Asymmetric Decision Problems," Management Science, Vol. 45, No. 11, 1999, pp. 1552--1569. DOI PDF (316K). A supplement to the published version is available (570 KB).

  • Giang, P. H. and P. P. Shenoy, "On Transformations Between Probability and Spohnian Disbelief Functions" in K. B. Laskey and H. Prade (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 15th Conference, 1999, pp. 236--244, Morgan Kaufmann, San Francisco, CA. PDF (2053 KB).
  • Schmidt, T. and P. P. Shenoy, "Some Improvements to the Shenoy-Shafer and Hugin Architectures for Computing Marginals," Artificial Intelligence, Vol. 102, No. 2, 1998, pp. 323--333. DOI PDF (129 KB).
  • Lepar, V. and P. P. Shenoy, "A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions" in G. Cooper and S. Moral (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 14th Conference, 1998, pp. 328--337, Morgan Kaufmann, San Francisco, CA. PDF (161 KB).
  • Shenoy, P. P., "Game Trees for Decision Analysis," Theory and Decision, Vol. 44, No. 2, 1998, pp. 149--171. DOI PDF (150 KB).
  • Shenoy, P. P., "Binary Join Trees for Computing Marginals in the Shenoy-Shafer Architecture," International Journal of Approximate Reasoning, Vol. 17, Nos. 2--3, 1997, pp. 239--263. DOI PDF (335 KB).
  • Guo, R. and P. P. Shenoy, "A Note on Kirkwood's Algebraic Method for Decision Problems," European Journal of Operational Research, Vol. 93, No. 3, 1996, pp. 628--638. DOI PDF (133 KB).
  • Shenoy, P. P., "Binary Join Trees," in E. Horvitz and F. V. Jensen (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 12th Conference, 1996, pp. 492--499, Morgan Kaufmann, San Francisco, CA. PDF
  • Shenoy, P. P., "Axioms for Dynamic Programming," in A. Gammerman (ed.), Computational Learning and Probabilistic Reasoning, 1996, pp. 259--275, John Wiley & Sons, Chichester. PDF (123 KB).
  • Shenoy, P. P., "Representing and Solving Asymmetric Decision Problems Using Valuation Networks," in D. Fisher and H.-J. Lenz (eds.), Learning from Data: Artificial Intelligence and Statistics V, Lecture Notes in Statistics, Vol. 112, 1996, pp. 99--108, Springer-Verlag, New York. DOI PDF (726 KB)
  • Shenoy, P. P., "A New Pruning Method for Solving Decision Trees and Game Trees," in P. Besnard and S. Hanks (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 11th Conference, 1995, pp. 482--490, Morgan Kaufmann, San Francisco, CA. PDF (142 KB).
  • Srivastava, R. P., P. P. Shenoy, and G. Shafer, "Propagating Belief Functions in AND-Trees," International Journal of Intelligent Systems, Vol. 10, No. 7, 1995, pp. 647--664. DOI PDF
  • Liu, L. and P. P. Shenoy, "A Theory of Coarse Utility," Journal of Risk and Uncertainty, Vol. 11, 1995, pp. 17--49. DOI PDF
  • Shenoy, P. P., "Modeling Ignorance in Uncertainty Theories," in Gammerman, A. (ed.), Probabilistic Reasoning and Bayesian Belief Networks, 1995, pp. 71--96, Alfred Waller, Henley-on-Thames, UK. PDF (1.4 MB)
  • Shenoy, P. P., "Consistency in Valuation-Based Systems," ORSA Journal on Computing, Vol. 6, No. 3, 1994, pp. 281--291. DOI PDF
  • Shenoy, P. P., "A Comparison of Graphical Techniques for Decision Analysis," European Journal of Operational Research, Vol. 78, No. 1, 1994, pp. 1--21. DOI PDF (630 KB).
  • Shenoy, P. P., "Representing Conditional Independence Relations by Valuation Networks," International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 2, No. 2, 1994, pp. 143--165. DOI PDF (3.1 MB)
  • Mishra, S. and P. P. Shenoy, "Attitude Formation Models: Insights from TETRAD," in P. Cheeseman and R. W. Oldford (eds.), Selecting Models from Data: Artificial Intelligence and Statistics IV, Lecture Notes in Statistics, Vol. 89, 1994, pp. 223--232, Springer-Verlag, New York. DOI PDF (783 KB)
  • Shenoy, P. P., "Conditional Independence in Valuation-Based Systems," International Journal of Approximate Reasoning, Vol. 10, No. 3, 1994, pp. 203--234. DOI PDF (641 KB).
  • Shenoy, P. P., "Using Dempster-Shafer's Belief-Function Theory in Expert Systems," in R. R. Yager, M. Federizzi, and J. Kacprzyk (eds.), Advances in the Dempster-Shafer Theory of Evidence, 1994, pp. 395--414, John Wiley & Sons, New York. PDF (149 KB).
  • Shenoy, P. P., "Information Sets in Decision Theory," in M. Clarke, R. Kruse and S. Moral (eds.), Symbolic and Quantitative Approaches to Reasoning and Uncertainty, Lecture Notes in Computer Science, Vol. 747, 1993, pp. 318--325, Springer-Verlag, Berlin. DOI
  • Shenoy, P. P., "Valuation Networks, Decision Trees, and Influence Diagrams: A Comparison," in B. Bouchon-Meunier, L. Valverde and R. R. Yager (eds.), Uncertainty in Intelligent Systems, 1993, pp. 3--14, North-Holland, Amsterdam. PDF (643 KB)
  • Shenoy, P. P., "Valuation Networks and Conditional Independence," in D. Heckerman and A. Mamdani (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 9th Conference, 1993, pp. 191--199, Morgan Kaufmann, San Mateo, CA. PDF (781 KB)
  • Shenoy, P. P., "A New Method for Representing and Solving Bayesian Decision Problems," in D. J. Hand (ed.), Artificial Intelligence Frontiers in Statistics: AI and Statistics III, 1993, pp. 119--138, Chapman & Hall, London. PDF (11MB)
  • Shenoy, P. P., "Using Possibility Theory in Expert Systems," Fuzzy Sets and Systems, Vol. 52, No. 2, 1992, pp. 129--142. DOI PDF (158 KB).
  • Shenoy, P. P., "Valuation-Based Systems: A Framework for Managing Uncertainty in Expert Systems," in L. A. Zadeh and J. Kacprzyk (eds.), Fuzzy Logic for the Management of Uncertainty, 1992, pp. 83--104, John Wiley & Sons, New York. DOI
  • Shenoy, P. P., "Conditional Independence in Uncertainty Theories," in D. Dubois, M. P. Wellman, B. D'Ambrosio and P. Smets (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 8th Conference, Vol. 8, 1992, pp. 284--291, Morgan Kaufmann, San Mateo, CA. PDF (688 KB)
  • Shenoy, P. P., "Valuation-Based Systems for Bayesian Decision Analysis," Operations Research, Vol. 40, No. 3, 1992, pp. 463--484. DOI PDF (3579 KB)
  • Shenoy, P. P., "On Spohn's Theory of Epistemic Beliefs," in B. Bouchon-Meunier, R. R. Yager and L. A. Zadeh (eds.), Uncertainty in Knowledge Bases, Lecture Notes in Computer Science, Vol. 521, 1991, pp. 2--13, Springer-Verlag, Berlin. DOI
  • Shenoy, P. P., "A Fusion Algorithm for Solving Bayesian Decision Problems," in B. D'Ambrosio, P. Smets and P. P. Bonissone (eds.), Uncertainty in Artificial Intelligence: Proceedings of the 7th Conference, 1991, pp. 361--369, Morgan Kaufmann, San Mateo, CA. PDF (530 KB)
  • Shenoy, P. P., "On Spohn's Rule for Revision of Beliefs," International Journal of Approximate Reasoning, Vol. 5, No. 2, 1991, pp. 149--181. DOI PDF (1.4MB)
  • Shenoy, P. P., "Valuation-Based Systems for Discrete Optimization," in P. P. Bonissone, M. Henrion, L. N. Kanal and J. F. Lemmer (eds.), Uncertainty in Artificial Intelligence 6, 1991, pp. 385--400, North-Holland, Amsterdam. WWW PDF
  • Shenoy, P. P., "Valuation-Based Systems for Propositional Logic," in Z. Ras, M. Zemankova and M. L. Emrich (eds.), Methodologies for Intelligent Systems, Vol. 5, 1990, pp. 305--312, North-Holland, Amsterdam. WWW
  • Shafer, G. R. and P. P. Shenoy, "Probability Propagation," Annals of Mathematics and Artificial Intelligence, Vol. 2, Nos. 1--4, 1990, pp. 327--352. DOI PDF (244 KB)
  • Shenoy, P. P. and G. Shafer, "Axioms for Probability and Belief-Function Propagation," in R. D. Shachter, T. Levitt, J. F. Lemmer and L. N. Kanal (eds.), Uncertainty in Artificial Intelligence, 4, 1990, pp. 169--198, North-Holland, Amsterdam. DOI PDF (233 KB)

    Reprinted in: G. Shafer and J. Pearl (eds.), Readings in Uncertain Reasoning, 1990, pp. 575-610, Morgan Kaufmann, San Mateo, CA.

    Also reprinted in: R. R. Yager and L. Liu (eds.), Classic Works of the Dempster-Shafer Theory of Belief Functions, Studies in Fuzziness and Soft Computing, Vol. 219, 2008, pp. 499--528, Springer-Verlag. DOI

  • Hsia, Y. and P. P. Shenoy, "An Evidential Language for Expert Systems," in Z. Ras (ed.), Methodologies for Intelligent Systems, Vol. 4, 1989, pp. 9--16, North-Holland, Amsterdam. MacEvidence (80 KB).
  • Shenoy, P. P., K. A. Shriver, and D. B. Smith, "The Potential Effects of Different Voting Rules on the FASB Due Process," in G. J. Previts (ed.), Research in Accounting Regulation, Vol. 3, 1989, pp. 125--132, JAI Press, Greenwich, CT. PDF
  • Shenoy, P. P., "A Valuation-Based Language for Expert Systems," International Journal of Approximate Reasoning, Vol. 3, No. 2, 1989, pp. 383--411. DOI PDF (1.3MB)
  • Shafer, G., P. P. Shenoy, and R. P. Srivastava, "Auditor's Assistant: A Knowledge Engineering Tool for Audit Decisions (with discussion)," in R. P. Srivastava and J. E. Rebele (eds.), Auditing Symposium IX: Proceedings of the 1988 Touche Ross/University of Kansas Symposium on Auditing Problems, 1988, pp. 61--83. PDF (2.8MB)
  • Shenoy, P. P., G. Shafer, and K. Mellouli, "Propagation of Belief Functions: A Distributed Approach," in J. F. Lemmer and L. N. Kanal (eds.), Uncertainty in Artificial Intelligence, 2, 1988, pp. 325--335, North-Holland, Amsterdam. PDF (444 KB)
  • Mellouli, K., G. Shafer, and P. P. Shenoy, "Qualitative Markov Networks," in B. Bouchon and R. R. Yager (eds.), Uncertainty in Knowledge-Based Systems, Lecture Notes in Computer Science, Vol. 286, 1987, pp. 69--74, Springer-Verlag, Berlin. DOI PDF
  • Cohen, P., G. Shafer, and P. P. Shenoy, "Modifiable Combining Functions," Artificial Intelligence for Engineering Design, Analysis, and Manufacturing, Vol. 1, No. 1, 1987, pp. 47--57. DOI PDF
  • Shafer, G., P. P. Shenoy, and K. Mellouli, "Propagating Belief Functions in Qualitative Markov Trees," International Journal of Approximate Reasoning, Vol. 1, No. 4, 1987, pp. 349--400. DOI PDF (2.7MB)
  • Shenoy, P. P., "Competitive Inventory Models," RAIRO-Operations Research, Vol. 21, No. 1, 1987, pp. 1--19. DOI PDF (1.4 MB)
  • Shenoy, P. P. and G. Shafer, "Propagating Belief Functions with Local Computations," IEEE Expert, Vol. 1, No. 3, 1986, pp. 43--52. DOI PDF (8.9MB)
  • Shenoy, P. P. and R. Martin, "Two Interpretations of the Difference Principle in Rawls' Theory of Justice," Theoria, Vol. 49, No. 3, 1983, pp. 113--141. DOI PDF
  • Shenoy, P. P., "The Banzhaf Power Index for Political Games," Mathematical Social Sciences, Vol. 2, No. 3, 1982, pp. 299--315. DOI PDF (1.3MB)
  • Shenoy, P. P., "A Solution for Noncooperative Games," Journal of Optimization Theory and Applications, Vol. 38, No. 4, 1982, pp. 565--579. DOI
  • Shenoy, P. P., and P.-L. Yu, "Inducing Cooperation by Reciprocative Strategy in Non-zero-sum Games," Journal of Mathematical Analysis and Applications, Vol. 80, No. 1, 1981, pp. 67--77. DOI PDF
  • Shenoy, P. P., "A three-person Cooperative Game Model of the World Oil Market," Applied Mathematical Modeling, Vol. 4, No. 4, 1980, pp. 301--307. DOI PDF
  • Shenoy, P. P., "A two-person Non-zero-sum Game Model of the World Oil Market," Applied Mathematical Modeling, Vol. 4, No. 4, 1980, pp. 295--300. DOI PDF
  • Shenoy, P. P., "A Dynamic Solution Concept for Abstract Games," Journal of Optimization Theory and Applications, Vol. 32, No. 2, 1980, pp. 151--169. DOI
  • Shenoy, P. P., "On Committee Decision Making: A Game-Theoretical Approach," Management Science, Vol. 26, No. 4, 1980, pp. 387--400. DOI PDF (1336 KB)
  • Shenoy, P. P., "On Coalition Formation: A Game-Theoretical Approach," International Journal of Game Theory, Vol. 8, No. 3, 1979, pp. 133--164. DOI PDF (1.32 MB)
  • Shenoy, P. P., "On Coalition Formation in Simple Games: A Mathematical Analysis of Caplow's and Gamson's Theories," Journal of Mathematical Psychology, Vol. 18, No. 2, 1978, pp. 177--194. DOI PDF (883KB)


PUBLICATIONS IN REFEREED PROCEEDINGS

  • Marsillach, D. A., S. Virani, M. J. Holzinger, M.W. Chan, and P. P. Shenoy, "Real-time Telescope Tasking for Custody and Anomaly Resolution using Judicial Evidential Reasoning," in Proceedings of 29th AAS/AIAA Space Flight Mechanics Meeting, AAS-534, 2019. PDF
  • Jaunzemis, A. D., M. J. Holzinger, M. W. Chan, and P. P. Shenoy, "Evidence Gathering for Hypothesis Resolution Using Judicial Evidential Reasoning," in Fusion-2018: Proceedings of the 21st International Conference on Information Fusion, pp. 2626--2633, IEEE, Piscataway, NJ. PDF (380 KB)
  • Shenoy, P. P., "An Expectation Operator for Belief Functions in the Dempster-Shafer Theory," in V. Kratochvíl and J. Vejnarová (eds.), Proceedings of the 11th Workshop on Uncertainty Processing, 2018, pp. 165--176, MatfyzPress, Praha, Czech Republic. PDF (303 KB)
  • Jiroušek, R. and P. P. Shenoy, "Ambiguity Aversion and a Decision-Theoretic Framework Using Belief Functions," in 2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, 2017, pp. 326--332, IEEE, Piscataway, NJ. PDF (1.76 MB)
  • Jaunzemis, A.D., D. Minotra, M. J. Holzinger, K. M. Feigh, M. W. Chan, and P. P. Shenoy, "Judicial Evidential Reasoning for Decision Support Applied to Orbit Insertion Failure," in First International Academy of Astronautics (IIA) Conference on Space Situational Awareness, 2017. PDF (946 KB)
  • Cobb, B. R. and P. P. Shenoy, "Piecewise Linear Approximations of Nonlinear Deterministic Conditionals in Continuous Bayesian Networks," in A. Cano, M. Gómez-Olmedo, and T. D. Nielsen (eds.), Proceedings of the 6th European Workshop on Probabilistic Graphical Models (PGM-12), 2012, pp. 59--66, DECSAI University of Granada, Spain. PDF (245 KB)
  • Rumí, R., A. Salmerón, and P. P. Shenoy, "Tractable Inference in Hybrid Bayesian Networks with Deterministic Conditionals Using Re-approximations," in A. Cano, M. Gómez-Olmedo, and T. D. Nielsen (eds.), Proceedings of the 6th European Workshop on Probabilistic Graphical Models (PGM-12), 2012, pp. 275--282, DECSAI University of Granada, Spain. PDF (540 KB)
  • Shenoy, P. P., R. Rumí, and A. Salmerón, "Some Practical Issues in Inference in Hybrid Bayesian Networks with Deterministic Conditionals," in S. Ventura, A. Abraham, K. Cios, C. Romero, F. Marcelloni, J. M. Benitez, and E. Gibaja (eds.), Proceedings of the 2011 Eleventh International Conference on Intelligent Systems Design and Applications (ISDA-11), 2011, pp. 605--610, IEEE Research Publishing Services, Piscataway, NJ. DOI PDF (999 KB).
  • Jiroušek, R. and P. P. Shenoy, "A note on factorization of belief functions," in R. Bartak (ed.), Proceedings of the Fourteenth Czech-Japan Seminar on Data Analysis and Decision Making Under Uncertainty (CJS-11), pp. 43--51, 2011, Matfyz Press, Charles University in Prague, CZ. PDF (319 KB).
  • Cinicioglu, E. N. and P. P. Shenoy, "Using Mixtures of Truncated Exponentials for Solving Stochastic PERT Networks," in J. Vejnarova and T. Kroupa (eds.), Proceedings of the Eighth Workshop on Uncertainty Processing (WUPES-09), pp. 269--283, 2009, University of Economics, Prague. PDF (209 KB).
  • Shenoy, P. P. and J. C. West, "Mixtures of Polynomials in Hybrid Bayesian Networks with Deterministic Variables," in J. Vejnarova and T. Kroupa (eds.), Proceedings of the Eighth Workshop on Uncertainty Processing (WUPES-09), pp. 202--212, 2009, University of Economics, Prague. PDF (651 KB).
  • Cinicioglu, E. N. and P. P. Shenoy, "Solving Stochastic PERT Networks Exactly Using Hybrid Bayesian Networks," in J. Vejnarova and T. Kroupa (eds.), Proceedings of the Seventh Workshop on Uncertainty Processing (WUPES-06), pp. 183--197, 2006, Mikulov, Czech Republic, Oeconomica Publishers. PDF (1151 KB).
  • Cinicioglu, E. N. and P. P. Shenoy, "On Walley's Combination Rule for Statistical Evidence," Proceedings of the Eleventh International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-06), pp. 386--394, 2006, Les Cordeliers, Paris, France. PDF (567 KB).
  • Shenoy, P. P., "No Double Counting Semantics for Conditional Independence," in F. G. Cozman, R. Nau, and T. Seidenfeld (eds.), Proceedings of the Fourth International Symposium on Imprecise Probabilities and Their Applications (ISIPTA-05), 2005, pp. 306--314, Society for Imprecise Probabilities and Their Applications. PDF (1009 KB).
  • Jensen, F. V., T. D. Nielsen, and P. P. Shenoy, "Sequential Influence Diagrams: A Unified Asymmetry Framework," in P. Lucas (ed.), Proceedings of the Second European Workshop on Probabilistic Graphical Models (PGM-04), pp. 121--128, 2004, Leiden, Netherlands. PDF (186 KB).
  • Cobb, B. R. and P. P. Shenoy, "Inference in Hybrid Bayesian Networks with Deterministic Variables," in P. Lucas (ed.), Proceedings of the Second European Workshop on Probabilistic Graphical Models (PGM-04), pp. 57--64, 2004, Leiden, Netherlands. PDF (203 KB).
  • Cobb, B. R., P. P. Shenoy, and R. Rumí, "Approximating Probability Density Functions with Mixtures of Truncated Exponentials," Proceedings of the Tenth International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-04), pp. 429--436, 2004, Perugia, Italy. PDF (376 KB).
  • Cobb, B. R. and P. P. Shenoy, "Inference in Hybrid Bayesian Networks with Mixtures of Truncated Exponentials," in J. Vejnarova (ed.), Proceedings of the Sixth Workshop on Uncertainty Processing (WUPES-03), pp. 47--63, 2003, Hejnice, Czech Republic, VSE-Oeconomica Publishers, ISBN 80-245-0546-0. PDF (284 KB).
  • Kemmerer, B., S. Mishra, and P. P. SHenoy, "Bayesian Causal Maps as Decision Aids in Venture Capital Decision Making: Methods and Applications," in Academy of Management Proceedings, Vol. 2002, No. 1, pp. C1--C6. DOI PDF (88 KB).
  • Liu, L. and P. P. Shenoy, "Conditional Belief Functions," Proceedings of the Decision Sciences Institute 1998 Annual Meeting, pp. 589--591, Las Vegas, NV. PDF (492KB)
  • Charnes, J. M. and P. P. Shenoy, "A Forward Monte Carlo Method for Solving Influence Diagrams Using Local Computation," Preliminary Papers of the Sixth International Workshop on Artificial Intelligence and Statistics, pp. 75--82, January 1997, Ft. Lauderdale, FL.
  • Bielza, C. and P. P. Shenoy, "A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems," Preliminary Papers of the Sixth International Workshop on Artificial Intelligence and Statistics, pp. 39--48, January 1997, Ft. Lauderdale, FL.
  • Liu, L. and P. P. Shenoy, "A Decomposition Method for Asymmetric Decision Problems," Proceedings of the Decision Sciences Institute 1995 Annual Meeting , Vol. 2, pp. 589--591, November 1995, Boston, MA.
  • Shenoy, P. P., "Representing and Solving Asymmetric Decision Problems Using Valuation Networks," Preliminary Papers of the Fifth International Workshop on Artificial Intelligence and Statistics, pp. 488--494, January 1995, Ft. Lauderdale, FL. PDF (937 KB)
  • Shenoy, P. P., "A New Pruning Method for Solving Decision Trees and Game Trees," Proceedings of the Third Workshop on Uncertainty Processing in Expert Systems, pp. 227--242, September 1994, Trest, Czech Republic.
  • Shenoy, P. P., "A Discussion of Kyburg's "Believing on the Basis of the Evidence," Computational Intelligence, Vol. 10, No. 1, pp. 92--93, 1994. DOI PDF (130 KB)
  • Shenoy, P. P., "Valuation Networks and Asymmetric Decision Problems," Proceedings of the Fifth International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Vol. 1, 1994, pp. 153--158, Paris, France.
  • Mishra, S. and P. P. Shenoy, "Searching for Alternative Representation of Data: A Case for TETRAD," in Preliminary Papers of the Fourth International Workshop on Artificial Intelligence and Statistics, pp. 375--380, January 1993, Fort Lauderdale, FL.
  • Shenoy, P. P., "Valuation Networks: A New Graphical Representation and Solution Technique for Decision Problems," in Knowledge-Based Construction of Probabilistic and Decision Models, Workshop Notes from the Ninth National Conference on Artificial Intelligence (AAAI-91), pp. 118--122, July 1991, Anaheim, CA.
  • Shenoy, P. P. and G. Biswas, "Belief Revision and Belief Maintenance in Artificial Intelligence: Guest Editors Introduction," International Journal of Approximate Reasoning, Vol. 4, No. 5--6, 1990, pp. 319-322. DOI PDF (179KB)
  • Shenoy, P. P. and R. P. Srivastava, "A Graphical System for Audit Planning and Evidence Aggregation," Proceedings of the Fifth Annual Conference on Making Statistics More Effective in Schools of Business, Lawrence, KS, June 1990, pp. 92--125.
  • Shenoy, P. P. and G. Shafer, "Constraint Propagation," Proceedings of the IJCAI-89 Workshop on Constraint Processing, Detroit, MI, July 1989, pp. 160--163.
  • Hsia, Y. and P. P. Shenoy, "MacEvidence: A Visual Environment for Constructing and Evaluating Evidential Systems," Proceedings of the World Conference on Information Processing and Communication (WOCON-INFOR 89), Seoul, South Korea, June 1989, pp. 20--25.
  • Shafer, G. and P. P. Shenoy, "A Discussion of Paper by Lauritzen and Spiegelhalter," Journal of Royal Statistical Society, Vol. 50, Series B, 1988, p. 214. PDF (4.5 MB)

UNPUBLISHED WORKING PAPERS

  • Shenoy, P. P., "Representing Piecewise Functions in Mathematica(c)," Working Paper No. 324, March 2011, School of Business, University of Kansas. PDF (225 KB).
  • Kemmerer, B., S. Mishra, and P. P. Shenoy, "Bayesian Causal Maps as Decision Aids in Venture Capital Decision Making: Methods and Applications," Working Paper No. 291, April 2002, School of Business, University of Kansas. PDF (113 KB)
  • Lander, D. M. and P. P. Shenoy, "Modeling and Valuing Real Options Using Influence Diagrams," Working Paper No. 283, School of Business, University of Kansas. PDF (232 KB).
  • Shafer, G. and P. P. Shenoy, "Local Computation in Hypertrees," Working Paper No. 201, August 1988, School of Business, University of Kansas. PDF (1921 KB).

Last updated Wednesday, August 19, 2020