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Linda C. van der Gaag
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- affiliation: Utrecht University, Netherlands
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2020 – today
- 2021
- [c89]Janneke H. Bolt, Linda C. van der Gaag:
Generalized Rules of Probabilistic Independence. ECSQARU 2021: 590-602 - 2020
- [j29]Zeynep Akata, Dan Balliet, Maarten de Rijke
, Frank Dignum, Virginia Dignum
, Guszti Eiben, Antske Fokkens
, Davide Grossi
, Koen V. Hindriks
, Holger H. Hoos, Hayley Hung, Catholijn M. Jonker, Christof Monz, Mark A. Neerincx, Frans A. Oliehoek
, Henry Prakken, Stefan Schlobach
, Linda C. van der Gaag, Frank van Harmelen
, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij
, Piek Vossen
, Max Welling:
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer 53(8): 18-28 (2020) - [j28]Linda C. van der Gaag, Marco Baioletti
, Janneke H. Bolt:
A lattice-based representation of independence relations for efficient closure computation. Int. J. Approx. Reason. 126: 272-289 (2020) - [j27]Giulianella Coletti, Linda C. van der Gaag, Davide Petturiti, Barbara Vantaggi
:
Detecting correlation between extreme probability events. Int. J. Gen. Syst. 49(1): 64-87 (2020) - [c88]Linda C. van der Gaag, Silja Renooij, Alessandro Facchini:
Building Causal Interaction Models by Recursive Unfolding. PGM 2020: 509-520 - [c87]Linda C. van der Gaag, Janneke H. Bolt:
Poset Representations for Sets of Elementary Triplets. PGM 2020: 521-532
2010 – 2019
- 2019
- [c86]Janneke H. Bolt, Linda C. van der Gaag:
On Minimum Elementary-Triplet Bases for Independence Relations. ISIPTA 2019: 32-37 - [c85]Alvaro Henrique Chaim Correia
, Cassio P. de Campos, Linda C. van der Gaag:
An Experimental Study of Prior Dependence in Bayesian Network Structure Learning. ISIPTA 2019: 78-81 - [c84]Silja Renooij, Linda C. van der Gaag, Philippe Leray:
On Intercausal Interactions in Probabilistic Relational Models. ISIPTA 2019: 327-329 - [c83]Silja Renooij
, Linda C. van der Gaag:
The Hidden Elegance of Causal Interaction Models. SUM 2019: 38-51 - 2018
- [c82]Linda C. van der Gaag, Marco Baioletti, Janneke H. Bolt:
A Lattice Representation of Independence Relations. PGM 2018: 487-498 - [c81]Linda C. van der Gaag, Andrea Capotorti:
Naive Bayesian Classifiers with Extreme Probability Features. PGM 2018: 499-510 - [c80]Linda C. van der Gaag, Philippe Leray
:
Qualitative Probabilistic Relational Models. SUM 2018: 276-289 - 2017
- [j26]Janneke H. Bolt, Linda C. van der Gaag:
Balanced sensitivity functions for tuning multi-dimensional Bayesian network classifiers. Int. J. Approx. Reason. 80: 361-376 (2017) - [j25]Stavros Lopatatzidis, Linda C. van der Gaag:
Concise representations and construction algorithms for semi-graphoid independency models. Int. J. Approx. Reason. 80: 377-392 (2017) - [c79]Remi Wieten, Floris Bex, Linda C. van der Gaag, Henry Prakken, Silja Renooij
:
Refining a Heuristic for Constructing Bayesian Networks from Structured Arguments. BNCAI 2017: 32-45 - [c78]Linda C. van der Gaag, Stavros Lopatatzidis:
Exploiting Stability for Compact Representation of Independency Models. ECSQARU 2017: 104-114 - 2016
- [j24]Andrés R. Masegosa, A. J. Feelders, Linda C. van der Gaag:
Learning from incomplete data in Bayesian networks with qualitative influences. Int. J. Approx. Reason. 69: 18-34 (2016) - 2015
- [j23]Steven P. D. Woudenberg, Linda C. van der Gaag:
Propagation effects of model-calculated probability values in Bayesian networks. Int. J. Approx. Reason. 61: 1-15 (2015) - [j22]Steven P. D. Woudenberg, Linda C. van der Gaag, Carin M. A. Rademaker:
An intercausal cancellation model for Bayesian-network engineering. Int. J. Approx. Reason. 63: 32-47 (2015) - [c77]Arnoud Pastink, Linda C. van der Gaag:
Multi-classifiers of Small Treewidth. ECSQARU 2015: 199-209 - [c76]Janneke H. Bolt, Linda C. van der Gaag:
Balanced Tuning of Multi-dimensional Bayesian Network Classifiers. ECSQARU 2015: 210-220 - [c75]Stavros Lopatatzidis, Linda C. van der Gaag:
Computing Concise Representations of Semi-graphoid Independency Models. ECSQARU 2015: 290-300 - [c74]Michelle Meekes, Silja Renooij
, Linda C. van der Gaag:
Relevance of Evidence in Bayesian Networks. ECSQARU 2015: 366-375 - 2014
- [c73]Thomas E. Krak, Linda C. van der Gaag:
Knowledge-based Bias Correction - A Case Study in Veterinary Decision Support. ECAI 2014: 489-494 - [c72]Arnoud Pastink, Linda C. van der Gaag:
The Persistence of Most Probable Explanations in Bayesian Networks. ECAI 2014: 693-698 - [c71]Merel T. Rietbergen, Linda C. van der Gaag, Hans L. Bodlaender
:
Provisional Propagation for Verifying Monotonicity of Bayesian Networks. ECAI 2014: 759-764 - [c70]Steven P. D. Woudenberg, Linda C. van der Gaag, Ad Feelders, Armin R. W. Elbers:
Real-time Adaptive Problem Detection in Poultry. ECAI 2014: 1217-1218 - [c69]Steven P. D. Woudenberg, Linda C. van der Gaag, Ad Feelders, Armin R. W. Elbers:
Real-Time Adaptive Residual Calculation for Detecting Trend Deviations in Systems with Natural Variability. IDA 2014: 380-392 - [e4]Linda C. van der Gaag, A. J. Feelders:
Probabilistic Graphical Models - 7th European Workshop, PGM 2014, Utrecht, The Netherlands, September 17-19, 2014. Proceedings. Lecture Notes in Computer Science 8754, Springer 2014, ISBN 978-3-319-11432-3 [contents] - 2013
- [e3]Linda C. van der Gaag:
Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 12th European Conference, ECSQARU 2013, Utrecht, The Netherlands, July 8-10, 2013. Proceedings. Lecture Notes in Computer Science 7958, Springer 2013, ISBN 978-3-642-39090-6 [contents] - [i19]Silja Renooij, Linda C. van der Gaag:
From Qualitative to Quantitative Probabilistic Networks. CoRR abs/1301.0596 (2013) - [i18]Hans L. Bodlaender, Arie M. C. A. Koster, Frank van den Eijkhof, Linda C. van der Gaag:
Pre-processing for Triangulation of Probabilistic Networks. CoRR abs/1301.2256 (2013) - [i17]Linda C. van der Gaag, Silja Renooij:
Analysing Sensitivity Data from Probabilistic Networks. CoRR abs/1301.2314 (2013) - [i16]Uffe Kjærulff, Linda C. van der Gaag:
Making Sensitivity Analysis Computationally Efficient. CoRR abs/1301.3868 (2013) - [i15]Silja Renooij, Linda C. van der Gaag, Simon Parsons, Shaw Green:
Pivotal Pruning of Trade-offs in QPNs. CoRR abs/1301.3889 (2013) - [i14]Silja Renooij, Linda C. van der Gaag:
Enhancing QPNs for Trade-off Resolution. CoRR abs/1301.6735 (2013) - [i13]Linda C. van der Gaag, Silja Renooij, Cilia Witteman, Berthe M. P. Aleman, Babs G. Taal:
How to Elicit Many Probabilities. CoRR abs/1301.6745 (2013) - [i12]Marek J. Druzdzel, Linda C. van der Gaag:
Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information. CoRR abs/1302.4943 (2013) - [i11]Linda C. van der Gaag:
Computing Probability Intervals Under Independency Constraints. CoRR abs/1304.1140 (2013) - 2012
- [c68]Linda C. van der Gaag, Silja Renooij
, Hermina Schijf, Armin Elbers, Willie Loeffen
:
Experiences with Eliciting Probabilities from Multiple Experts. IPMU (3) 2012: 151-160 - [c67]Roel Bertens, Linda C. van der Gaag, Silja Renooij
:
Discretisation Effects in Naive Bayesian Networks. IPMU (3) 2012: 161-170 - [i10]Johan Kwisthout, Linda C. van der Gaag:
The Computational Complexity of Sensitivity Analysis and Parameter Tuning. CoRR abs/1206.3265 (2012) - [i9]Theodore Charitos, Linda C. van der Gaag:
Sensitivity Analysis for Threshold Decision Making with Dynamic Networks. CoRR abs/1206.6818 (2012) - [i8]Peter R. de Waal, Linda C. van der Gaag:
Stable Independence in Perfect Maps. CoRR abs/1207.1351 (2012) - [i7]Silja Renooij, Linda C. van der Gaag:
Exploiting Evidence-dependent Sensitivity Bounds. CoRR abs/1207.1357 (2012) - [i6]Ad Feelders, Linda C. van der Gaag:
Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences. CoRR abs/1207.1387 (2012) - [i5]Peter R. de Waal, Linda C. van der Gaag:
Stable Independance and Complexity of Representation. CoRR abs/1207.4120 (2012) - [i4]Linda C. van der Gaag, Hans L. Bodlaender, Ad Feelders:
Monotonicity in Bayesian Networks. CoRR abs/1207.4160 (2012) - [i3]Silja Renooij, Linda C. van der Gaag:
Evidence-invariant Sensitivity Bounds. CoRR abs/1207.4170 (2012) - [i2]Ronald Parr, Linda C. van der Gaag:
Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (2007). CoRR abs/1208.5155 (2012) - [i1]Janneke H. Bolt, Silja Renooij, Linda C. van der Gaag:
Upgrading Ambiguous Signs in QPNs. CoRR abs/1212.2445 (2012) - 2011
- [c66]Steven P. D. Woudenberg, Linda C. van der Gaag:
Using the Noisy-OR Model Can Be Harmful ... But It Often Is Not. ECSQARU 2011: 122-133 - [c65]Merel T. Rietbergen, Linda C. van der Gaag:
Attaining Monotonicity for Bayesian Networks. ECSQARU 2011: 134-145 - [c64]Linda C. van der Gaag, Hans L. Bodlaender
:
On Stopping Evidence Gathering for Diagnostic Bayesian Networks. ECSQARU 2011: 170-181 - [c63]Barbara F. I. Pieters, Linda C. van der Gaag, Ad Feelders:
When Learning Naive Bayesian Classifiers Preserves Monotonicity. ECSQARU 2011: 422-433 - [c62]Johan Kwisthout, Hans L. Bodlaender
, Linda C. van der Gaag:
The Complexity of Finding kth Most Probable Explanations in Probabilistic Networks. SOFSEM 2011: 356-367 - 2010
- [j21]Linda C. van der Gaag, Hermina J. M. Tabachneck-Schijf:
Library-style ontologies to support varying model views. Int. J. Approx. Reason. 51(2): 196-208 (2010) - [c61]Johan Kwisthout, Hans L. Bodlaender, Linda C. van der Gaag:
The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks. ECAI 2010: 237-242 - [c60]Janneke H. Bolt, Linda C. van der Gaag:
An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network. IPMU (1) 2010: 11-20 - [c59]Linda C. van der Gaag, Janneke H. Bolt, Willie Loeffen
, Armin Elbers:
Modelling Patterns of Evidence in Bayesian Networks: A Case-Study in Classical Swine Fever. IPMU 2010: 675-684
2000 – 2009
- 2009
- [j20]Theodore Charitos, Linda C. van der Gaag, Stefan Visscher, Karin Schurink, Peter J. F. Lucas:
A dynamic Bayesian network for diagnosing ventilator-associated pneumonia in ICU patients. Expert Syst. Appl. 36(2): 1249-1258 (2009) - [j19]Linda C. van der Gaag, Russell G. Almond:
Preface. Int. J. Approx. Reason. 50(3): 415 (2009) - [j18]Linda C. van der Gaag, Hermina J. M. Tabachneck-Schijf, Petra L. Geenen:
Verifying monotonicity of Bayesian networks with domain experts. Int. J. Approx. Reason. 50(3): 429-436 (2009) - [c58]Linda C. van der Gaag, Silja Renooij
, Wilma Steeneveld, Henk Hogeveen
:
When in Doubt ... Be Indecisive. ECSQARU 2009: 518-529 - [c57]Linda C. van der Gaag, Silja Renooij
, Ad Feelders, Arend de Groote, Marinus J. C. Eijkemans, Frank J. Broekmans, Bart C. J. M. Fauser:
Aligning Bayesian Network Classifiers with Medical Contexts. MLDM 2009: 787-801 - 2008
- [j17]Silja Renooij
, Linda C. van der Gaag:
Enhanced qualitative probabilistic networks for resolving trade-offs. Artif. Intell. 172(12-13): 1470-1494 (2008) - [j16]Silja Renooij
, Linda C. van der Gaag:
Evidence and scenario sensitivities in naive Bayesian classifiers. Int. J. Approx. Reason. 49(2): 398-416 (2008) - [c56]Johan Kwisthout, Linda C. van der Gaag:
The Computational Complexity of Sensitivity Analysis and Parameter Tuning. UAI 2008: 349-356 - 2007
- [j15]Theodore Charitos, Peter R. de Waal, Linda C. van der Gaag:
Convergence in Markovian models with implications for efficiency of inference. Int. J. Approx. Reason. 46(2): 300-319 (2007) - [j14]Eveline M. Helsper, Linda C. van der Gaag:
Ontologies for probabilistic networks: a case study in the oesophageal-cancer domain. Knowl. Eng. Rev. 22(1): 67-86 (2007) - [c55]Danielle Sent, Linda C. van der Gaag:
On the Behaviour of Information Measures for Test Selection. AIME 2007: 316-325 - [c54]Danielle Sent, Linda C. van der Gaag:
Enhancing Automated Test Selection in Probabilistic Networks. AIME 2007: 331-335 - [c53]Peter R. de Waal, Linda C. van der Gaag:
Inference and Learning in Multi-dimensional Bayesian Network Classifiers. ECSQARU 2007: 501-511 - [c52]Hermina J. M. Tabachneck-Schijf, Linda C. van der Gaag:
Library-style Ontologies to Support Varying Model Views. BMA 2007 - [e2]Ronald Parr, Linda C. van der Gaag:
UAI 2007, Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence, Vancouver, BC, Canada, July 19-22, 2007. AUAI Press 2007, ISBN 0-9749039-3-0 [contents] - 2006
- [j13]A. J. Feelders, Linda C. van der Gaag:
Learning Bayesian network parameters under order constraints. Int. J. Approx. Reason. 42(1-2): 37-53 (2006) - [c51]Theodore Charitos, Linda C. van der Gaag:
Sensitivity Analysis of Markovian Models. FLAIRS 2006: 806-811 - [c50]Danielle Sent, Linda C. van der Gaag:
Automated Test Selection in Decision-Support Systems: a Case Study in Oncology. MIE 2006: 491-496 - [c49]Janneke H. Bolt, Linda C. van der Gaag:
Preprocessing the MAP Problem. Probabilistic Graphical Models 2006: 51-58 - [c48]Linda C. van der Gaag, Silja Renooij, Petra L. Geenen:
Lattices for Studying Monotonicity of Bayesian Networks. Probabilistic Graphical Models 2006: 99-106 - [c47]Linda C. van der Gaag, Peter R. de Waal:
Multi-dimensional Bayesian Network Classifiers. Probabilistic Graphical Models 2006: 107-114 - [c46]Silja Renooij, Linda C. van der Gaag:
Evidence and Scenario Sensitivities in Naive Bayesian Classifiers. Probabilistic Graphical Models 2006: 255-262 - [c45]Theodore Charitos, Linda C. van der Gaag:
Sensitivity Analysis for Threshold Decision Making with Dynamic Networks. UAI 2006 - 2005
- [j12]Danielle Sent, Linda C. van der Gaag:
Generalised reliability characteristics for probabilistic networks. Artif. Intell. Medicine 34(1): 41-52 (2005) - [j11]Janneke H. Bolt, Linda C. van der Gaag, Silja Renooij
:
Introducing situational signs in qualitative probabilistic networks. Int. J. Approx. Reason. 38(3): 333-354 (2005) - [c44]Theodore Charitos, Peter R. de Waal, Linda C. van der Gaag:
Speeding Up Inference in Markovian Models. FLAIRS 2005: 785-790 - [c43]Martijn M. Schrage, Arjan van IJzendoorn, Linda C. van der Gaag:
Haskell ready to dazzle the real world. Haskell 2005: 17-26 - [c42]Eveline M. Helsper, Linda C. van der Gaag, A. J. Feelders, Willie Loeffen
, Petra L. Geenen, Armin Elbers:
Bringing order into bayesian-network construction. K-CAP 2005: 121-128 - [c41]Peter R. de Waal, Linda C. van der Gaag:
Stable Independence in Perfect Maps. UAI 2005: 161-168 - [c40]A. J. Feelders, Linda C. van der Gaag:
Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences. UAI 2005: 193-200 - [c39]Silja Renooij, Linda C. van der Gaag:
Exploiting Evidence-dependent Sensitivity Bounds. UAI 2005: 485-492 - 2004
- [j10]Peter J. F. Lucas, Linda C. van der Gaag, Ameen Abu-Hanna
:
Bayesian networks in biomedicine and health-care. Artif. Intell. Medicine 30(3): 201-214 (2004) - [c38]Madalina M. Drugan, Linda C. van der Gaag:
A New MDL-Based Function for Feature Selection for Bayesian Network Classifiers. ECAI 2004: 999-1000 - [c37]Linda C. van der Gaag, Eveline M. Helsper:
Defining Classes of Influences for the Acquisition of Probability Constraints for Bayesian Networks. ECAI 2004: 1101-1102 - [c36]Eveline M. Helsper, Linda C. van der Gaag, Floris Groenendaal:
Designing a Procedure for the Acquisition of Probability Constraints for Bayesian Networks. EKAW 2004: 280-292 - [c35]Petra L. Geenen, Linda C. van der Gaag, Willie Loeffen, Armin Elbers:
On the Robustness of Feature Selection with Absent and Non-observed Features. ISBMDA 2004: 148-159 - [c34]Rosa Blanco, Linda C. van der Gaag, Iñaki Inza
, Pedro Larrañaga
:
Selective Classifiers Can Be Too Restrictive: A Case-Study in Oesophageal Cancer. ISBMDA 2004: 212-223 - [c33]Peter R. de Waal, Linda C. van der Gaag:
Stable Independance and Complexity of Representation. UAI 2004: 112-119 - [c32]Silja Renooij, Linda C. van der Gaag:
Evidence-invariant Sensitivity Bounds. UAI 2004: 479-486 - [c31]Linda C. van der Gaag, Hans L. Bodlaender, A. J. Feelders:
Monotonicity in Bayesian Networks. UAI 2004: 569-576 - 2003
- [c30]Danielle Sent, Linda C. van der Gaag:
Detailing Test Characteristics for Probabilistic Networks. AIME 2003: 254-263 - [c29]Linda C. van der Gaag, Silja Renooij
:
Probabilistic Networks as Probabilistic Forecasters. AIME 2003: 294-298 - [c28]Wouter P. van Rijsinge, Linda C. van der Gaag, Frank L. J. Visseren, Yolanda van der Graaf:
Compliance with the Hyperlipidaemia Consensus: Clinicians versus the Computer. AIME 2003: 340-344 - [c27]Janneke H. Bolt, Linda C. van der Gaag, Silja Renooij
:
Introducing Situational Influences in QPNs. ECSQARU 2003: 113-124 - [c26]Steven van Dijk, Dirk Thierens, Linda C. van der Gaag:
Building a GA from Design Principles for Learning Bayesian Networks. GECCO 2003: 886-897 - [c25]Danielle Sent, Linda C. van der Gaag, Cilia Witteman, Berthe M. P. Aleman, Babs G. Taal:
On the Use of Vignettes for Eliciting Test-Selection Strategies. MIE 2003: 510-515 - [c24]Steven van Dijk, Linda C. van der Gaag, Dirk Thierens:
A Skeleton-Based Approach to Learning Bayesian Networks from Data. PKDD 2003: 132-143 - [c23]Janneke H. Bolt, Silja Renooij, Linda C. van der Gaag:
Upgrading Ambiguous Signs in QPNs. UAI 2003: 73-80 - 2002
- [j9]Silja Renooij
, Linda C. van der Gaag, Simon Parsons:
Context-specific sign-propagation in qualitative probabilistic networks. Artif. Intell. 140(1/2): 207-230 (2002) - [j8]Veerle M. H. Coupé, Linda C. van der Gaag:
Properties of Sensitivity Analysis of Bayesian Belief Networks. Ann. Math. Artif. Intell. 36(4): 323-356 (2002) - [j7]Linda C. van der Gaag, Silja Renooij
, C. L. M. Witteman, Berthe M. P. Aleman, Babs G. Taal:
Probabilities for a probabilistic network: a case study in oesophageal cancer. Artif. Intell. Medicine 25(2): 123-148 (2002) - [c22]Silja Renooij, Linda C. van der Gaag, Simon Parsons:
Propagation of Multiple Observations in QPNs Revisited. ECAI 2002: 665-669 - [c21]Hans L. Bodlaender, Frank van den Eijkhof, Linda C. van der Gaag:
On the Complexity of the MPA Problem in Probabilistic Networks. ECAI 2002: 675-679 - [c20]Eveline M. Helsper, Linda C. van der Gaag:
Building Bayesian Networks through Ontologies. ECAI 2002: 680-684 - [c19]Linda C. van der Gaag, Eveline M. Helsper:
Experiences with Modelling Issues in Building Probabilistic Networks. EKAW 2002: 21-26 - [c18]Silja Renooij, Linda C. van der Gaag:
From Qualitative to Quantitative Probabilistic Networks. UAI 2002: 422-429 - 2001
- [c17]Linda C. van der Gaag, C. L. M. Witteman, Silja Renooij
, Michael Egmont-Petersen:
The Effects of Disregarding Test Characteristics in Probabilistic Networks. AIME 2001: 188-198 - [c16]Linda C. van der Gaag, Silja Renooij
:
On the Evaluation of Probabilistic Networks. AIME 2001: 457-461 - [c15]Silja Renooij, Simon Parsons, Linda C. van der Gaag:
Context-specific Sign-propagation in Qualitative Probabilistic Networks. IJCAI 2001: 667-672 - [c14]Hans L. Bodlaender, Arie M. C. A. Koster, Frank van den Eijkhof, Linda C. van der Gaag:
Pre-processing for Triangulation of Probabilistic Networks. UAI 2001: 32-39 - [c13]Linda C. van der Gaag, Silja Renooij:
Analysing Sensitivity Data from Probabilistic Networks. UAI 2001: 530-537 - 2000
- [c12]Silja Renooij, Linda C. van der Gaag, Shaw Green, Simon Parsons:
Zooming in on Trade-Offs in Qualitative Probabilistic Networks. FLAIRS 2000: 303-307 - [c11]Uffe Kjærulff, Linda C. van der Gaag:
Making Sensitivity Analysis Computationally Efficient. UAI 2000: 317-325 - [c10]Silja Renooij, Linda C. van der Gaag, Simon Parsons, Shaw Green:
Pivotal Pruning of Trade-offs in QPNs. UAI 2000: 515-522 - [e1]Marek J. Druzdzel
, Linda C. van der Gaag:
Building Probabilistic Networks: "Where Do the Numbers Come From?" Guest Editors Introduction. IEEE Trans. Knowl. Data Eng. 12(4): 481-486 (2000)
1990 – 1999
- 1999
- [c9]Linda C. van der Gaag, Veerle M. H. Coupé:
Sensitive Analysis for Threshold Decision Making with Bayesian Belief Networks. AI*IA 1999: 37-48 - [c8]Silja Renooij, Linda C. van der Gaag:
Enhancing QPNs for Trade-off Resolution. UAI 1999: 559-566 - [c7]Linda C. van der Gaag, Silja Renooij, C. L. M. Witteman, Berthe M. P. Aleman, Babs G. Taal:
How to Elicit Many Probabilities. UAI 1999: 647-654 - 1998
- [j6]Linda C. van der Gaag, John-Jules Ch. Meyer:
Informational independence: Models and normal forms. Int. J. Intell. Syst. 13(1): 83-109 (1998) - [c6]Silja Renooij, Linda C. van der Gaag:
Decision Making in Qualitative Influence Diagrams. FLAIRS 1998: 410-414 - 1997
- [c5]Veerle M. H. Coupé, Linda C. van der Gaag:
Supporting Probability Elicitation by Sensitivity Analysis. EKAW 1997: 335-340 - 1996
- [j5]Linda C. van der Gaag:
Bayesian Belief Networks: Odds and Ends. Comput. J. 39(2): 97-113 (1996) - [j4]Linda C. van der Gaag:
On evidence absorption for belief networks. Int. J. Approx. Reason. 15(3): 265-286 (1996) - 1995
- [c4]Niels Peek, Linda C. van der Gaag:
A Case-based Filter for Diagnostic Belief Networks. SCAI 1995: 196-207 - [c3]Marek J. Druzdzel, Linda C. van der Gaag:
Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information. UAI 1995: 141-148 - 1993
- [j3]Gerry Kelleher, Linda C. van der Gaag:
The LazyRMS: Avoiding Work in the ATMS. Comput. Intell. 9: 239-253 (1993) - [c2]Peter Bruza
, Linda C. van der Gaag:
Efficient Context-Sensitive Plausible Inference for Information Disclosure. SIGIR 1993: 12-21 - 1991
- [b1]Peter J. F. Lucas, Linda C. van der Gaag:
Principles of expert systems. International computer science series, Addison-Wesley 1991, ISBN 978-0-201-41640-4, pp. I-XVII, 1-518 - 1990
- [j2]Linda C. van der Gaag:
Different Notions of Uncertainty in Quasi-Probabilistic Models. Int. J. Man Mach. Stud. 33(5): 595-606 (1990) - [c1]Linda C. van der Gaag:
Computing probability intervals under independency constraints. UAI 1990: 457-466
1980 – 1989
- 1989
- [j1]Linda C. van der Gaag:
A conceptual model for inexact reasoning in rule-based systems. Int. J. Approx. Reason. 3(3): 239-258 (1989)
Coauthor Index
aka: Ad Feelders
![](https://dblp1.uni-trier.de/img/cog.dark.24x24.png)
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last updated on 2024-05-02 21:46 CEST by the dblp team
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