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Prakash P. Shenoy
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2020 – today
- 2024
- [j62]Yi Tan, Ben Sherwood, Prakash P. Shenoy:
A naïve Bayes regularized logistic regression estimator for low-dimensional classification. Int. J. Approx. Reason. 172: 109239 (2024) - [j61]Yi Tan
, Prakash P. Shenoy
Bayesian Network Models for PTSD Screening in Veterans. INFORMS J. Comput. 36(2): 495-509 (2024) - [c49]Prakash P. Shenoy
Mutual Information and Kullback-Leibler Divergence in the Dempster-Shafer Theory. BELIEF 2024: 225-233 - 2023
- [j60]Prakash P. Shenoy
Making inferences in incomplete Bayesian networks: A Dempster-Shafer belief function approach. Int. J. Approx. Reason. 160: 108967 (2023) - [j59]Radim Jirousek, Václav Kratochvíl
On conditional belief functions in directed graphical models in the Dempster-Shafer theory. Int. J. Approx. Reason. 160: 108976 (2023) - [j58]Radim Jirousek, Václav Kratochvíl
Computing the decomposable entropy of belief-function graphical models. Int. J. Approx. Reason. 161: 108984 (2023) - [c48]Radim Jirousek, Václav Kratochvíl, Prakash P. Shenoy:
On the relationship between graphical and compositional models for the Dempster-Shafer theory of belief functions. ISIPTA 2023: 259-269 - [c47]Prakash P. Shenoy:
On distinct belief functions in the Dempster-Shafer theory. ISIPTA 2023: 426-437 - 2022
- [j57]John C. Aldrich, A. Philip Dawid, Thierry Denoeux
Probability and statistics: Foundations and history. Special Issue in honor of Glenn Shafer. Int. J. Approx. Reason. 141: 1-4 (2022) - [j56]John C. Aldrich, A. Philip Dawid, Thierry Denoeux, Prakash P. Shenoy
Glenn Shafer - A short biography. Int. J. Approx. Reason. 141: 5-10 (2022) - [j55]Radim Jirousek
Entropy for evaluation of Dempster-Shafer belief function models. Int. J. Approx. Reason. 151: 164-181 (2022) - [c46]Radim Jirousek
On Conditional Belief Functions in the Dempster-Shafer Theory. BELIEF 2022: 207-218 - 2021
- [c45]Radim Jirousek
Entropy-Based Learning of Compositional Models from Data. BELIEF 2021: 117-126 - 2020
- [j54]Yi Tan, Prakash P. Shenoy
A bias-variance based heuristic for constructing a hybrid logistic regression-naïve Bayes model for classification. Int. J. Approx. Reason. 117: 15-28 (2020) - [j53]Radim Jirousek, Prakash P. Shenoy
On properties of a new decomposable entropy of Dempster-Shafer belief functions. Int. J. Approx. Reason. 119: 260-279 (2020) - [j52]Thierry Denoeux
An interval-valued utility theory for decision making with Dempster-Shafer belief functions. Int. J. Approx. Reason. 124: 194-216 (2020) - [j51]Prakash P. Shenoy
An expectation operator for belief functions in the Dempster-Shafer theory. Int. J. Gen. Syst. 49(1): 112-141 (2020)
2010 – 2019
- 2019
- [j50]Andris Davis Jaunzemis, Marcus J. Holzinger, Moses W. Chan, Prakash P. Shenoy
Evidence gathering for hypothesis resolution using judicial evidential reasoning. Inf. Fusion 49: 26-45 (2019) - [c44]Thierry Denoeux, Prakash P. Shenoy:
An Axiomatic Utility Theory for Dempster-Shafer Belief Functions. ISIPTA 2019: 145-155 - [i22]Thierry Denoeux, Prakash P. Shenoy
An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Functions. CoRR abs/1912.06594 (2019) - 2018
- [j49]Radim Jirousek, Prakash P. Shenoy
A new definition of entropy of belief functions in the Dempster-Shafer theory. Int. J. Approx. Reason. 92: 49-65 (2018) - [j48]Sumanta Singha
An adaptive heuristic for feature selection based on complementarity. Mach. Learn. 107(12): 2027-2071 (2018) - [c43]Radim Jirousek, Prakash P. Shenoy
A Decomposable Entropy of Belief Functions in the Dempster-Shafer Theory. BELIEF 2018: 146-154 - [c42]Radim Jirousek, Prakash P. Shenoy
Combination and Composition in Probabilistic Models. ECONVN 2018: 120-133 - [c41]Andris Davis Jaunzemis, Marcus J. Holzinger, Moses W. Chan, Prakash P. Shenoy
Evidence Gathering for Hypothesis Resolution Using Judicial Evidential Reasoning. FUSION 2018: 1-8 - 2017
- [j47]Sumanta Singha, Steve Hillmer, Prakash P. Shenoy
On computing probabilities of dismissal of 10b-5 securities class-action cases. Decis. Support Syst. 94: 29-41 (2017) - [j46]Barry R. Cobb, Prakash P. Shenoy
Inference in Hybrid Bayesian Networks with Nonlinear Deterministic Conditionals. Int. J. Intell. Syst. 32(12): 1217-1246 (2017) - [c40]Radim Jirousek, Prakash P. Shenoy
Ambiguity aversion and a decision-theoretic framework using belief functions. SSCI 2017: 1-7 - 2016
- [j45]Esma Nur Cinicioglu
A new heuristic for learning Bayesian networks from limited datasets: a real-time recommendation system application with RFID systems in grocery stores. Ann. Oper. Res. 244(2): 385-405 (2016) - [j44]Radim Jirousek, Prakash P. Shenoy
Causal compositional models in valuation-based systems with examples in specific theories. Int. J. Approx. Reason. 72: 95-112 (2016) - [c39]Radim Jirousek, Prakash P. Shenoy
Entropy of Belief Functions in the Dempster-Shafer Theory: A New Perspective. BELIEF 2016: 3-13 - [c38]Yi Tan, Prakash P. Shenoy, Moses W. Chan, Paul M. Romberg:
On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification. Probabilistic Graphical Models 2016: 523-534 - 2015
- [j43]Prakash P. Shenoy
Practical Aspects of Solving Hybrid Bayesian Networks Containing Deterministic Conditionals. Int. J. Intell. Syst. 30(3): 265-291 (2015) - 2014
- [j42]Radim Jirousek, Prakash P. Shenoy
Compositional models in valuation-based systems. Int. J. Approx. Reason. 55(1): 277-293 (2014) - [c37]Radim Jirousek, Prakash P. Shenoy
Causal Compositional Models in Valuation-Based Systems. Belief Functions 2014: 256-264 - 2013
- [i21]Phan Hong Giang, Prakash P. Shenoy:
Statistical Decisions Using Likelihood Information Without Prior Probabilities. CoRR abs/1301.0569 (2013) - [i20]Phan Hong Giang, Prakash P. Shenoy:
A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory. CoRR abs/1301.2271 (2013) - [i19]Phan Hong Giang, Prakash P. Shenoy:
A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs. CoRR abs/1301.3858 (2013) - [i18]Phan Hong Giang, Prakash P. Shenoy:
On Transformations between Probability and Spohnian Disbelief Functions. CoRR abs/1301.6699 (2013) - [i17]Vasilica Lepar, Prakash P. Shenoy:
A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions. CoRR abs/1301.7394 (2013) - [i16]Prakash P. Shenoy:
Binary Join Trees. CoRR abs/1302.3604 (2013) - [i15]Prakash P. Shenoy:
A New Pruning Method for Solving Decision Trees and Game Trees. CoRR abs/1302.4981 (2013) - [i14]Prakash P. Shenoy:
Valuation Networks and Conditional Independence. CoRR abs/1303.1477 (2013) - [i13]Prakash P. Shenoy:
Conditional Independence in Uncertainty Theories. CoRR abs/1303.5429 (2013) - [i12]Prakash P. Shenoy:
A Fusion Algorithm for Solving Bayesian Decision Problems. CoRR abs/1303.5750 (2013) - [i11]Prakash P. Shenoy, Glenn Shafer:
Valuation-Based Systems for Discrete Optimization. CoRR abs/1304.1121 (2013) - [i10]Prakash P. Shenoy, Glenn Shafer:
An Axiomatic Framework for Bayesian and Belief-function Propagation. CoRR abs/1304.2374 (2013) - [i9]Paul R. Cohen, Glenn Shafer, Prakash P. Shenoy:
Modifiable Combining Functions. CoRR abs/1304.2712 (2013) - [i8]Prakash P. Shenoy, Glenn Shafer, Khaled Mellouli:
Propagation of Belief Functions: A Distributed Approach. CoRR abs/1304.3109 (2013) - [i7]Dan Geiger, Prakash P. Shenoy:
Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (1997). CoRR abs/1304.3846 (2013) - 2012
- [j41]Yijing Li, Prakash P. Shenoy
A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions. Decis. Anal. 9(1): 55-75 (2012) - [j40]Prakash P. Shenoy
Two issues in using mixtures of polynomials for inference in hybrid Bayesian networks. Int. J. Approx. Reason. 53(5): 847-866 (2012) - [c36]Radim Jirousek, Prakash P. Shenoy
Compositional Models in Valuation-Based Systems. Belief Functions 2012: 221-228 - [c35]Radim Jirousek, Prakash P. Shenoy
Conditioning in Decomposable Compositional Models in Valuation-Based Systems. IPMU (4) 2012: 676-685 - [i6]Yijing Li, Prakash P. Shenoy:
Solving Hybrid Influence Diagrams with Deterministic Variables. CoRR abs/1203.3493 (2012) - [i5]Prakash P. Shenoy:
Inference in Hybrid Bayesian Networks Using Mixtures of Gaussians. CoRR abs/1206.6877 (2012) - [i4]Barry R. Cobb, Prakash P. Shenoy:
Hybrid Bayesian Networks with Linear Deterministic Variables. CoRR abs/1207.1369 (2012) - [i3]Barry R. Cobb, Prakash P. Shenoy:
Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials. CoRR abs/1207.4177 (2012) - [i2]Liping Liu, Catherine Shenoy, Prakash P. Shenoy:
A Linear Belief Function Approach to Portfolio Evaluation. CoRR abs/1212.2473 (2012) - [i1]Phan Hong Giang, Prakash P. Shenoy:
Decision Making with Partially Consonant Belief Functions. CoRR abs/1212.2484 (2012) - 2011
- [j39]Phan Hong Giang, Prakash P. Shenoy
A decision theory for partially consonant belief functions. Int. J. Approx. Reason. 52(3): 375-394 (2011) - [j38]Prakash P. Shenoy
Inference in hybrid Bayesian networks using mixtures of polynomials. Int. J. Approx. Reason. 52(5): 641-657 (2011) - [j37]Prakash P. Shenoy
Extended Shenoy-Shafer architecture for inference in hybrid bayesian networks with deterministic conditionals. Int. J. Approx. Reason. 52(6): 805-818 (2011) - [c34]Prakash P. Shenoy
A Re-definition of Mixtures of Polynomials for Inference in Hybrid Bayesian Networks. ECSQARU 2011: 98-109 - [c33]Prakash P. Shenoy
Some practical issues in inference in hybrid Bayesian networks with deterministic conditionals. ISDA 2011: 605-610 - 2010
- [j36]Concha Bielza
Modeling challenges with influence diagrams: Constructing probability and utility models. Decis. Support Syst. 49(4): 354-364 (2010) - [c32]Yijing Li, Prakash P. Shenoy:
Solving Hybrid Influence Diagrams with Deterministic Variables. UAI 2010: 322-331
2000 – 2009
- 2009
- [j35]Esma Nur Cinicioglu
Arc reversals in hybrid Bayesian networks with deterministic variables. Int. J. Approx. Reason. 50(5): 763-777 (2009) - [c31]Prakash P. Shenoy
Inference in Hybrid Bayesian Networks with Deterministic Variables. ECSQARU 2009: 46-58 - 2008
- [j34]Barry R. Cobb, Prakash P. Shenoy
Decision making with hybrid influence diagrams using mixtures of truncated exponentials. Eur. J. Oper. Res. 186(1): 261-275 (2008) - [p1]Prakash P. Shenoy
Axioms for Probability and Belief-Function Propagation. Classic Works of the Dempster-Shafer Theory of Belief Functions 2008: 499-528 - 2007
- [j33]Lili Sun, Prakash P. Shenoy
Using Bayesian networks for bankruptcy prediction: Some methodological issues. Eur. J. Oper. Res. 180(2): 738-753 (2007) - [c30]Esma Nur Cinicioglu
Use of Radio Frequency Identification for Targeted Advertising: A Collaborative Filtering Approach Using Bayesian Networks. ECSQARU 2007: 889-900 - 2006
- [j32]Riza Demirer
Sequential valuation networks for asymmetric decision problems. Eur. J. Oper. Res. 169(1): 286-309 (2006) - [j31]Barry R. Cobb, Prakash P. Shenoy
Inference in hybrid Bayesian networks with mixtures of truncated exponentials. Int. J. Approx. Reason. 41(3): 257-286 (2006) - [j30]Barry R. Cobb, Prakash P. Shenoy
On the plausibility transformation method for translating belief function models to probability models. Int. J. Approx. Reason. 41(3): 314-330 (2006) - [j29]Barry R. Cobb, Prakash P. Shenoy
Operations for inference in continuous Bayesian networks with linear deterministic variables. Int. J. Approx. Reason. 42(1-2): 21-36 (2006) - [j28]Finn Verner Jensen, Thomas D. Nielsen
Sequential influence diagrams: A unified asymmetry framework. Int. J. Approx. Reason. 42(1-2): 101-118 (2006) - [j27]Barry R. Cobb, Prakash P. Shenoy
Approximating probability density functions in hybrid Bayesian networks with mixtures of truncated exponentials. Stat. Comput. 16(3): 293-308 (2006) - [j26]Liping Liu, Catherine Shenoy, Prakash P. Shenoy
Knowledge representation and integration for portfolio evaluation using linear belief functions. IEEE Trans. Syst. Man Cybern. Part A 36(4): 774-785 (2006) - [c29]Prakash P. Shenoy:
Inference in Hybrid Bayesian Networks Using Mixtures of Gaussians. UAI 2006 - 2005
- [j25]Phan Hong Giang, Prakash P. Shenoy
Decision making on the sole basis of statistical likelihood. Artif. Intell. 165(2): 137-163 (2005) - [j24]Phan Hong Giang, Prakash P. Shenoy
Two axiomatic approaches to decision making using possibility theory. Eur. J. Oper. Res. 162(2): 450-467 (2005) - [c28]Barry R. Cobb, Prakash P. Shenoy
Nonlinear Deterministic Relationships in Bayesian Networks. ECSQARU 2005: 27-38 - [c27]Prakash P. Shenoy:
No Double Counting Semantics for Conditional Independence. ISIPTA 2005: 306-314 - [c26]Barry R. Cobb, Prakash P. Shenoy:
Hybrid Bayesian Networks with Linear Deterministic Variables. UAI 2005: 136-144 - 2004
- [j23]Liping Liu, Prakash P. Shenoy
Representing asymmetric decision problems using coarse valuations. Decis. Support Syst. 37(1): 119-135 (2004) - [j22]Sucheta Nadkarni, Prakash P. Shenoy
A causal mapping approach to constructing Bayesian networks. Decis. Support Syst. 38(2): 259-281 (2004) - [j21]John M. Charnes, Prakash P. Shenoy
Multistage Monte Carlo Method for Solving Influence Diagrams Using Local Computation. Manag. Sci. 50(3): 405-418 (2004) - [c25]Barry R. Cobb, Prakash P. Shenoy:
Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials. UAI 2004: 85-93 - 2003
- [j20]Prakash P. Shenoy
Application of Uncertain Reasoning to Business Decisions: An Introduction. Inf. Syst. Frontiers 5(4): 343-344 (2003) - [j19]Barry R. Cobb, Prakash P. Shenoy
A Comparison of Bayesian and Belief Function Reasoning. Inf. Syst. Frontiers 5(4): 345-358 (2003) - [c24]Barry R. Cobb, Prakash P. Shenoy
A Comparison of Methods for Transforming Belief Function Models to Probability Models. ECSQARU 2003: 255-266 - [c23]Phan Hong Giang, Prakash P. Shenoy:
Decision Making with Partially Consonant Belief Functions. UAI 2003: 272-280 - [c22]Liping Liu, Catherine Shenoy, Prakash P. Shenoy:
A Linear Belief Function Approach to Portfolio Evaluation. UAI 2003: 370-377 - 2002
- [c21]Phan Hong Giang, Prakash P. Shenoy:
Statistical Decisions Using Likelihood Information Without Prior Probabilities. UAI 2002: 170-178 - 2001
- [j18]Sucheta Nadkarni, Prakash P. Shenoy
A Bayesian network approach to making inferences in causal maps. Eur. J. Oper. Res. 128(3): 479-498 (2001) - [c20]Riza Demirer
Sequential Valuation Networks: A New Graphical Technique for Asymmetric Decision Problems. ECSQARU 2001: 252-265 - [c19]Phan Hong Giang, Prakash P. Shenoy:
A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory. UAI 2001: 162-170 - 2000
- [j17]Prakash P. Shenoy
Valuation network representation and solution of asymmetric decision problems. Eur. J. Oper. Res. 121(3): 579-608 (2000) - [c18]Phan Hong Giang, Prakash P. Shenoy:
A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs. UAI 2000: 220-229
1990 – 1999
- 1999
- [c17]Phan Hong Giang, Prakash P. Shenoy:
On Transformations between Probability and Spolinian Disbelief Functions. UAI 1999: 236-244 - 1998
- [j16]Tuija Schmidt, Prakash P. Shenoy
Some Improvements to the Shenoy-Shafer and Hugin Architectures for Computing Marginals. Artif. Intell. 102(2): 323-333 (1998) - [c16]Vasilica Lepar, Prakash P. Shenoy:
A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions. UAI 1998: 328-337 - 1997
- [j15]Prakash P. Shenoy
Binary join trees for computing marginals in the Shenoy-Shafer architecture. Int. J. Approx. Reason. 17(2-3): 239-263 (1997) - [c15]Concha Bielza, Prakash P. Shenoy:
A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems. AISTATS 1997: 39-46 - [c14]John M. Charnes, Prakash P. Shenoy:
A Forward Monte Carlo Method for Solving Influence Diagrams using local Computation. AISTATS 1997: 75-82 - [e1]Dan Geiger, Prakash P. Shenoy:
UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, Brown University, Providence, Rhode Island, USA, August 1-3, 1997. Morgan Kaufmann 1997, ISBN 1-55860-485-5 [contents] - 1996
- [c13]Prakash P. Shenoy:
Binary Join Trees. UAI 1996: 492-499 - 1995
- [j14]Rajendra P. Srivastava, Prakash P. Shenoy
Propagating belief functions in AND-trees. Int. J. Intell. Syst. 10(7): 647-664 (1995) - [c12]Prakash P. Shenoy
Representing and Solving Asymmetric Decision Problems Using Valuation Networks. AISTATS 1995: 99-108 - [c11]Prakash P. Shenoy:
A New Pruning Method for Solving Decision Trees and Game Trees. UAI 1995: 482-490 - 1994
- [j13]Prakash P. Shenoy
Discussion of Kyburg's "Believing on the Basis of Evidence". Comput. Intell. 10: 92-93 (1994) - [j12]Prakash P. Shenoy
Conditional independence in valuation-based systems. Int. J. Approx. Reason. 10(3): 203-234 (1994) - [j11]Prakash P. Shenoy
Representing Conditional Independence Relations by Valuation Networks. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 2(2): 143-166 (1994) - [j10]Prakash P. Shenoy
Consistency in Valuation-Based Systems. INFORMS J. Comput. 6(3): 281-291 (1994) - 1993
- [c10]Prakash P. Shenoy
Information Sets in Decision Theory. ECSQARU 1993: 318-325 - [c9]Prakash P. Shenoy:
Valuation Networks and Conditional Independence. UAI 1993: 191-199 - 1992
- [j9]Prakash P. Shenoy
Valuation-Based Systems for Bayesian Decision Analysis. Oper. Res. 40(3): 463-484 (1992) - [c8]Prakash P. Shenoy:
Conditional lndependence in Uncertainty Theories. UAI 1992: 284-291 - 1991
- [j8]Prakash P. Shenoy
On Spohn's rule for revision of beliefs. Int. J. Approx. Reason. 5(2): 149-181 (1991) - [c7]Prakash P. Shenoy:
A Fusion Algorithm for Solving Bayesian Decision Problems. UAI 1991: 361-369 - 1990
- [j7]Glenn Shafer, Prakash P. Shenoy
Probability propagation. Ann. Math. Artif. Intell. 2: 327-351 (1990) - [j6]Prakash P. Shenoy
Belief functions and belief maintenance in artificial intelligence. Int. J. Approx. Reason. 4(5-6): 319-322 (1990) - [c6]Prakash P. Shenoy
On Spohn's Theory of Epistemic Beliefs. IPMU 1990: 2-13 - [c5]Prakash P. Shenoy:
Valuation-based systems for discrete optimisation. UAI 1990: 385-400
1980 – 1989
- 1989
- [j5]Prakash P. Shenoy
A valuation-based language for expert systems. Int. J. Approx. Reason. 3(5): 383-411 (1989) - 1988
- [c4]Prakash P. Shenoy, Glenn Shafer:
Axioms for probability and belief-function proagation. UAI 1988: 169-198 - 1987
- [j4]Paul R. Cohen, Glenn Shafer, Prakash P. Shenoy
Modifiable combining functions. Artif. Intell. Eng. Des. Anal. Manuf. 1(1): 47-57 (1987) - [j3]Glenn Shafer, Prakash P. Shenoy
Propagating belief functions in qualitative Markov trees. Int. J. Approx. Reason. 1(4): 349-400 (1987) - [c3]Paul R. Cohen, Glenn Shafer, Prakash P. Shenoy:
Modifiable Combining Functions. UAI 1987: 357-374 - 1986
- [j2]Prakash P. Shenoy
Propagating Belief Functions with Local Computations. IEEE Expert 1(3): 43-52 (1986) - [c2]Khaled Mellouli, Glenn Shafer, Prakash P. Shenoy
Qualitative Markov networks. IPMU 1986: 69-74 - [c1]Prakash P. Shenoy, Glenn Shafer, Khaled Mellouli:
Propagation of belief functions: a distributed approach. UAI 1986: 325-336 - 1982
- [j1]Prakash P. Shenoy
The Banzhaf power index for political games. Math. Soc. Sci. 2(3): 299-315 (1982)
Coauthor Index
Glenn Shafer
aka: Glenn R. Shafer
aka: Glenn R. Shafer
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