Stan Matwin

Kambiz Ghazinour, Stan Matwin, Marina Sokolova: Monitoring and recommending privacy settings in social networks. EDBT/ICDT Workshops 2013: 164-168

Stan Matwin: Privacy-Preserving Data Mining Techniques: Survey and Challenges. Discrimination and Privacy in the Information Society 2013: 209-221

Jin Huang, Jelber Sayyad-Shirabad, Stan Matwin, Jiang Su: Improving multi-view semi-supervised learning with agreement-based sampling. Intell. Data Anal. 16(5): 745-761 (2012)

Stan Matwin, Vera Sazonova: Direct comparison between support vector machine and multinomial naive Bayes algorithms for medical abstract classification. JAMIA 19(5): 917 (2012)

Bernard Stepien, Stan Matwin, Amy P. Felty: An Algorithm for Compression of XACML Access Control Policy Sets by Recursive Subsumption. ARES 2012: 161-167

Erico N. de Souza, Stan Matwin: Improvements to AdaBoost Dynamic. Canadian Conference on AI 2012: 293-298

Xiaoguang Wang, Hang Shao, Nathalie Japkowicz, Stan Matwin, Xuan Liu, Alex Bourque, Bao Nguyen: Using SVM with Adaptively Asymmetric MisClassification Costs for Mine-Like Objects Detection. ICMLA (2) 2012: 78-82

Ahmed Ali Abdalla Esmin, Roberto L. De Oliveira Jr., Stan Matwin: Hierarchical Classification Approach to Emotion Recognition in Twitter. ICMLA (2) 2012: 381-385

Ahmed Ali Abdalla Esmin, Stan Matwin: Data Clustering Using Hybrid Particle Swarm Optimization. IDEAL 2012: 159-166

Oana Frunza, Diana Inkpen, Stan Matwin, William Klement, Peter O'Blenis: Exploiting the systematic review protocol for classification of medical abstracts. Artificial Intelligence in Medicine 51(1): 17-25 (2011)

Mikhail Jiline, Stan Matwin, Marcel Turcotte: Annotation concept synthesis and enrichment analysis: a logic-based approach to the interpretation of high-throughput experiments. Bioinformatics 27(17): 2391-2398 (2011)

Stan Matwin, Alexandre Kouznetsov, Diana Inkpen, Oana Frunza, Peter O'Blenis: Letter: Performance of SVM and Bayesian classifiers on the systematic review classification task. JAMIA 18(1): 104-105 (2011)

William Klement, Szymon Wilk, Wojtek Michalowski, Stan Matwin: Classifying Severely Imbalanced Data. Canadian Conference on AI 2011: 258-264

Erico N. de Souza, Stan Matwin: Extending AdaBoost to Iteratively Vary Its Base Classifiers. Canadian Conference on AI 2011: 384-389

Jiang Su, Jelber Sayyad Shirab, Stan Matwin: Large Scale Text Classification using Semisupervised Multinomial Naive Bayes. ICML 2011: 97-104

William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin: Smooth Receiver Operating Characteristics (smROC) Curves. ECML/PKDD (2) 2011: 193-208

Bernard Stepien, Stan Matwin, Amy P. Felty: Advantages of a non-technical XACML notation in role-based models. PST 2011: 193-200

Javier Herranz, Stan Matwin, Jordi Nin, Vicenç Torra: Classifying data from protected statistical datasets. Computers & Security 29(8): 875-890 (2010)

Stan Matwin, Alexandre Kouznetsov, Diana Inkpen, Oana Frunza, Peter O'Blenis: A new algorithm for reducing the workload of experts in performing systematic reviews. JAMIA 17(4): 446-453 (2010)

Ken Farion, Wojtek Michalowski, Szymon Wilk, Dympna O'Sullivan, Stan Matwin: A Tree-Based Decision Model to Support Prediction of the Severity of Asthma Exacerbations in Children. J. Medical Systems 34(4): 551-562 (2010)

Bernard Stepien, Stan Matwin, Amy P. Felty: Strategies for Reducing Risks of Inconsistencies in Access Control Policies. ARES 2010: 140-147

Amir Hossein Razavi, Diana Inkpen, Sasha Uritsky, Stan Matwin: Offensive Language Detection Using Multi-level Classification. Canadian Conference on AI 2010: 16-27

Houman Abbasian, Chris Drummond, Nathalie Japkowicz, Stan Matwin: Robustness of Classifiers to Changing Environments. Canadian Conference on AI 2010: 232-243

Mikhail Jiline, Stan Matwin, Marcel Turcotte: Annotation Concept Synthesis and Enrichment Analysis. Canadian Conference on AI 2010: 304-308

Farid Seifi, Chris Drummond, Nathalie Japkowicz, Stan Matwin: Improving Bayesian Learning Using Public Knowledge. Canadian Conference on AI 2010: 348-351

Oana Frunza, Diana Inkpen, Stan Matwin: Building Systematic Reviews Using Automatic Text Classification Techniques. COLING (Posters) 2010: 303-311

Stan Matwin, Joseph De Koninck, Amir Hossein Razavi, Ray Reza Amini: Classification of Dreams Using Machine Learning. ECAI 2010: 169-174

Jin Huang, Jelber Sayyad-Shirabad, Stan Matwin, Jiang Su: Improving Co-training with Agreement-Based Sampling. RSCTC 2010: 197-206

Stan Matwin, Tomasz Szapiro: Data Privacy: From Technology to Economics. Advances in Machine Learning II 2010: 43-74

Stan Matwin: Privacy-Related Aspects and Techniques. Encyclopedia of Machine Learning 2010: 795-801

William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin: Cost-Based Sampling of Individual Instances. Canadian Conference on AI 2009: 86-97

Alexandre Kouznetsov, Stan Matwin, Diana Inkpen, Amir Hossein Razavi, Oana Frunza, Morvarid Sehatkar, Leanne Seaward, Peter O'Blenis: Classifying Biomedical Abstracts Using Committees of Classifiers and Collective Ranking Techniques. Canadian Conference on AI 2009: 224-228

Jiang Su, Jelber Sayyad-Shirabad, Stan Matwin, Jin Huang: Active Learning with Automatic Soft Labeling for Induction of Decision Trees. Canadian Conference on AI 2009: 241-244

Javier Herranz, Stan Matwin, Pedro Meseguer, Jordi Nin: A Cryptographic Solution for Private Distributed Simple Meeting Scheduling. CCIA 2009: 275-283

Stan Matwin: Privacy and Data Mining: New Developments and Challenges. EGC 2009: 1

Amir Hossein Razavi, Stan Matwin, Diana Inkpen, Alexandre Kouznetsov: Parameterized Contrast in Second Order Soft Co-occurrences: A Novel Text Representation Technique in Text Mining and Knowledge Extraction. ICDM Workshops 2009: 471-476

Stan Matwin: Image Analysis and Machine Learning: How to Foster a Stronger Connection? ICIAP 2009: 5

Bernard Stepien, Amy P. Felty, Stan Matwin: A Non-technical User-Oriented Display Notation for XACML Conditions. MCETECH 2009: 53-64

Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwin: Discriminative parameter learning for Bayesian networks. ICML 2008: 1016-1023

Sylvain Létourneau, Stan Matwin, A. Fazel Famili: Generation of Globally Relevant Continuous Features for Classification. PAKDD 2008: 196-208

Jin Huang, Charles X. Ling, Harry Zhang, Stan Matwin: Proper Model Selection with Significance Test. ECML/PKDD (1) 2008: 536-547

Justin Zhijun Zhan, LiWu Chang, Stan Matwin: How to Prevent Private Data from being Disclosed to a Malicious Attacker. Data Mining: Foundations and Practice 2008: 517-528

Justin Zhijun Zhan, Stan Matwin, LiWu Chang: Privacy-Preserving Naive Bayesian Classification over Horizontally Partitioned Data. Data Mining: Foundations and Practice 2008: 529-538

Aijun An, Stan Matwin, Zbigniew W. Ras, Dominik Slezak (Eds.): Foundations of Intelligent Systems, 17th International Symposium, ISMIS 2008, Toronto, Canada, May 20-23, 2008, Proceedings. Lecture Notes in Computer Science 4994, Springer 2008, isbn 978-3-540-68122-9

Justin Zhijun Zhan, Stan Matwin, LiWu Chang: Privacy-preserving multi-party decision tree induction. IJBIDM 2(2): 197-212 (2007)

Justin Zhijun Zhan, Stan Matwin: Privacy-preserving support vector machine classification. IJIIDS 1(3/4): 356-385 (2007)

Justin Zhijun Zhan, Stan Matwin: Privacy-Preserving Data Mining in Electronic Surveys. I. J. Network Security 4(3): 318-327 (2007)

Justin Zhijun Zhan, Stan Matwin, LiWu Chang: Privacy-preserving collaborative association rule mining. J. Network and Computer Applications 30(3): 1216-1227 (2007)

Dympna O'Sullivan, Ken Farion, Stan Matwin, Wojtek Michalowski, Szymon Wilk: A Concept-Based Framework for Retrieving Evidence to Support Emergency Physician Decision Making at the Point of Care. K4CARE 2007: 117-126

Venanzio Capretta, Bernard Stepien, Amy P. Felty, Stan Matwin: Formal correctness of conflict detection for firewalls. FMSE 2007: 22-30

Dympna O'Sullivan, William Elazmeh, Szymon Wilk, Ken Farion, Stan Matwin, Wojtek Michalowski, Morvarid Sehatkar: Using Secondary Knowledge to Support Decision Tree Classification of Retrospective Clinical Data. MCD 2007: 238-251

Joost N. Kok, Jacek Koronacki, Ramon López de Mántaras, Stan Matwin, Dunja Mladenic, Andrzej Skowron (Eds.): Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings. Lecture Notes in Computer Science 4701, Springer 2007, isbn 978-3-540-74957-8

Joost N. Kok, Jacek Koronacki, Ramon López de Mántaras, Stan Matwin, Dunja Mladenic, Andrzej Skowron (Eds.): Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings. Lecture Notes in Computer Science 4702, Springer 2007, isbn 978-3-540-74975-2

Chris Drummond, Stan Matwin, Chad Gaffield: Inferring and revising theories with confidence: analyzing bilingualism in the 1901 canadian census. Applied Artificial Intelligence 20(1): 1-33 (2006)

Jerffeson Teixeira de Souza, Stan Matwin, Nathalie Japkowicz: Parallelizing Feature Selection. Algorithmica 45(3): 433-456 (2006)

David Nadeau, Peter D. Turney, Stan Matwin: Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity. Canadian Conference on AI 2006: 266-277

Maria Fernanda Caropreso, Stan Matwin: Beyond the Bag of Words: A Text Representation for Sentence Selection. Canadian Conference on AI 2006: 324-335

Svetlana Kiritchenko, Stan Matwin, Richard Nock, A. Fazel Famili: Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization. Canadian Conference on AI 2006: 395-406

William Elazmeh, Nathalie Japkowicz, Stan Matwin: Evaluating Misclassifications in Imbalanced Data. ECML 2006: 126-137

Justin Zhijun Zhan, Stan Matwin: A Crypto-Based Approach to Privacy-Preserving Collaborative Data Mining. ICDM Workshops 2006: 546-550

Justin Zhijun Zhan, Stan Matwin: Privacy-Oriented Collaborative Learning Systems. SMC 2006: 4102-4105

Justin Zhijun Zhan, LiWu Chang, Stan Matwin: Privacy-Preserving Collaborative Data Mining. Foundations and Novel Approaches in Data Mining 2006: 213-227

Justin Zhijun Zhan, LiWu Chang, Stan Matwin: Privacy Preserving K-nearest Neighbor Classification. I. J. Network Security 1(1): 46-51 (2005)

Quintin Armour, William Elazmeh, Nour El-Kadri, Nathalie Japkowicz, Stan Matwin: Privacy Compliance Enforcement in Email. Canadian Conference on AI 2005: 194-204

Guillaume Dufay, Amy P. Felty, Stan Matwin: Privacy-Sensitive Information Flow with JML. CADE 2005: 116-130

Narjès Boufaden, William Elazmeh, Yimin Ma, Stan Matwin, Nour El-Kadri, Nathalie Japkowicz: PEEP- An Information Extraction base approach for Privacy Protection in Email. CEAS 2005

Justin Zhijun Zhan, Stan Matwin, LiWu Chang: Privacy-Preserving Collaborative Association Rule Mining. DBSec 2005: 153-165

Justin Zhijun Zhan, LiWu Chang, Stan Matwin: Building k-nearest neighbor classifiers on vertically partitioned private data. GrC 2005: 708-711

Justin Zhijun Zhan, Stan Matwin, LiWu Chang: Private Mining of Association Rules. ISI 2005: 72-80

Jerffeson Teixeira de Souza, Nathalie Japkowicz, Stan Matwin: STochFS: A Framework for Combining Feature Selection Outcomes Through a Stochastic Process. PKDD 2005: 667-674

Narjès Boufaden, William Elazmeh, Stan Matwin, Nathalie Japkowicz: PEEP- Privacy Enforcement in Email Project. PST 2005

Stan Matwin, Amy P. Felty, István T. Hernádvölgyi, Venanzio Capretta: Privacy in Data Mining Using Formal Methods. TLCA 2005: 278-292

M. Ouerd, B. John Oommen, Stan Matwin: A formal approach to using data distributions for building causal polytree structures. Inf. Sci. 168(1-4): 111-132 (2004)

Érick Alphonse, Stan Matwin: Filtering Multi-Instance Problems to Reduce Dimensionality in Relational Learning. J. Intell. Inf. Syst. 22(1): 23-40 (2004)

Stan Matwin: Guest Editorial. Machine Learning 57(3): 203-204 (2004)

Justin Zhijun Zhan, LiWu Chang, Stan Matwin: Privacy-Preserving Multi-Party Decision Tree Induction. DBSec 2004: 341-355

Justin Zhijun Zhan, LiWu Chang, Stan Matwin: Bayesian Network Induction With Incomplete Private Data. ICEB 2004: 1119-1124

Justin Zhijun Zhan, Stan Matwin, Nathalie Japkowicz, LiWu Chang: Privacy-Preserving Collaborative Association Rule Mining. ICEB 2004: 1172-1178

Justin Zhijun Zhan, Stan Matwin: Privacy-Preserving Data Mining in Electronic Surveys. ICEB 2004: 1179-1185

Svetlana Kiritchenko, Stan Matwin, Suhayya Abu-Hakima: Email Classification with Temporal Features. Intelligent Information Systems 2004: 523-533

Jelber Sayyad-Shirabad, Stan Matwin, Timothy C. Lethbridge: Predictive Software Models. STEP 2004: 10-22

Marvin Zaluski, Nathalie Japkowicz, Stan Matwin: Case Authoring from Text and Historical Experiences. Canadian Conference on AI 2003: 222-236

Ouerd Messaouda, B. John Oommen, Stan Matwin: Enhancing Caching in Distributed Databases Using Intelligent Polytree Representations. Canadian Conference on AI 2003: 498-504

Jelber Sayyad-Shirabad, Timothy C. Lethbridge, Stan Matwin: Applying data mining to software maintenance records. CASCON 2003: 253-265

Jelber Sayyad-Shirabad, Timothy Lethbridge, Stan Matwin: Mining the Maintenance History of a Legacy Software System. ICSM 2003: 95-104

Stan Matwin, Claude Sammut (Eds.): Inductive Logic Programming, 12th International Conference, ILP 2002, Sydney, Australia, July 9-11, 2002. Revised Papers. Lecture Notes in Computer Science 2583, Springer 2003, isbn 3-540-00567-6

Svetlana Kiritchenko, Stan Matwin: Generalized Features: Their Application to Classification. AAAI/IAAI 2002: 985

Érick Alphonse, Stan Matwin: Feature Subset Selection and Inductive Logic Programming. ICML 2002: 11-18

Érick Alphonse, Stan Matwin: A Dynamic Approach to Dimensionality Reduction in Relational Learning. ISMIS 2002: 255-264

Amy P. Felty, Stan Matwin: Privacy-Oriented Data Mining by Proof Checking. PKDD 2002: 138-149

Johanne Morin, Stan Matwin: GENEX: a tool for testing in ILP. Softw., Pract. Exper. 31(10): 1003-1023 (2001)

Svetlana Kiritchenko, Stan Matwin: Email classification with co-training. CASCON 2001: 8

Svetlana Kiritchenko, Stan Matwin: Email classification with co-training. CASCON 2001: 301-312

J. Shirabad, Timothy Lethbridge, Stan Matwin: Supporting Software Maintenance by Mining Software Update Records. ICSM 2001: 22-31

Eleni Stroulia, Stan Matwin (Eds.): Advances in Artificial Intelligence, 14th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2001, Ottawa, Canada, June 7-9, 2001, Proceedings. Lecture Notes in Computer Science 2056, Springer 2001, isbn 3-540-42144-0

Johanne Morin, Stan Matwin: Relational Learning with Transfer of Knowledge Between Domains. Canadian Conference on AI 2000: 379-388

Jelber Sayyad-Shirabad, Timothy C. Lethbridge, Stan Matwin: Supporting maintenance of legacy software with data mining techniques. CASCON 2000: 11

Gregory E. Kersten, Stan Matwin, Sunil J. Noronha, Mik Kersten: The Software for Cultures and the Cultures in Software. ECIS 2000: 509-514

Johanne Morin, Stan Matwin: Learning Relational Clichés with Contextual LGG. ISMIS 2000: 274-282

M. Ouerd, B. John Oommen, Stan Matwin: A Formalism for Building Causal Polytree Structures Using Data Distributions. ISMIS 2000: 629-637

Sam Scott, Stan Matwin: Feature Engineering for Text Classification. ICML 1999: 379-388

Mauricio Amaral de Almeida, Stan Matwin: Machine Learning Method for Software Quality Model Building. ISMIS 1999: 565-573

Miroslav Kubat, Robert C. Holte, Stan Matwin: Machine Learning for the Detection of Oil Spills in Satellite Radar Images. Machine Learning 30(2-3): 195-215 (1998)

Sylvain Delisle, Sylvain Létourneau, Stan Matwin: Experiments with Learning Parsing Heuristics. COLING-ACL 1998: 307-314

Riverson Rios, Stan Matwin: Predicate Invention from a Few Examples. Canadian Conference on AI 1998: 455-466

Sylvain Létourneau, Stan Matwin, Fazel Famili: A Normalization Method for Contextual Data: Experience from a Large-Scale Application. ECML 1998: 49-54

Peter Clark, Cao Feng, Stan Matwin, Ko Fung: Improving Image Classification by Combining Statistical, Case-Based and Model Based Prediction Methods. Fundam. Inform. 30(3/4): 227-240 (1997)

Miroslav Kubat, Robert C. Holte, Stan Matwin: Learning When Negative Examples Abound. ECML 1997: 146-153

Miroslav Kubat, Stan Matwin: Addressing the Curse of Imbalanced Training Sets: One-Sided Selection. ICML 1997: 179-186

Daniel Charlebois, David G. Goodenough, Stan Matwin, A. S. (Pal) Bhogal, Hugh Barclay: Planning and Learning in a Natural Resource Information System. Canadian Conference on AI 1996: 187-199

Riverson Rios, Stan Matwin: Efficient Induction of Recursive Prolog Definitons. Canadian Conference on AI 1996: 240-248

Cindy L. Mason, Stan Matwin: Guest Editors' Introduction: Environmental Applications of AI. IEEE Expert 10(6): 12-13 (1995)

Stan Matwin, Daniel Charlebois, David G. Goodenough, A. S. (Pal) Bhogal: Machine Learning and Planning for Data Management in Forestry. IEEE Expert 10(6): 35-40 (1995)

Xiaobin Li, Stan Szpakowicz, Stan Matwin: A WordNet-based Algorithm for Word Sense Disambiguation. IJCAI 1995: 1368-1374

David W. Aha, Stephane Lapointe, Charles X. Ling, Stan Matwin: Inverting Implication with Small Training Sets. ECML 1994: 31-48

David W. Aha, Stephane Lapointe, Charles X. Ling, Stan Matwin: Learning Recursive Relations with Randomly Selected Small Training Sets. ICML 1994: 12-18

Stan Matwin, Affa Ahmad: Reuse of Modular Software with Automated Comment Analysis. ICSM 1994: 222-231

Gilles Fouqué, Stan Matwin: A Case-Based Approach to Software Reuse. J. Intell. Inf. Syst. 2(2): 165-197 (1993)

Peter Clark, Stan Matwin: Learning Domain Theories using Abstract Beckground Knowledge. ECML 1993: 360-365

Peter Clark, Stan Matwin: Using Qualitative Models to Guide Inductive Learning. ICML 1993: 49-56

R. Jetzelsperger, Stan Matwin, Franz Oppacher: Enhancing Reuse of Smalltalk Methods by Conceptual Clustering. ICTAI 1993: 108-112

Stephane Lapointe, Charles X. Ling, Stan Matwin: Constructive Inductive Logic Programming. IJCAI 1993: 1030-1036

Stephane Lapointe, Stan Matwin: Sub-unification: A Tool for Efficient Induction of Recursive Programs. ML 1992: 273-281

Stan Matwin, Tomasz Szapiro, Karen Zita Haigh: Genetic algorithms approach to a negotiation support system. IEEE Transactions on Systems, Man, and Cybernetics 21(1): 102-114 (1991)

Sylvain Delisle, Stan Matwin, Lionel Zupan: Integrating EBL with automatic Text Analysis. EWSL 1991: 347

Mary Gick, Stan Matwin: The Importance of Causal Structure and Facts in Evaluating Explanations. ML 1991: 51-54

Sylvain Delisle, Stan Matwin, Jiandong Wang, Lionel Zupan: Explanation-based Learning Helps Acquire Knowledge from Natural Language Texts. ISMIS 1991: 326-337

C. Geldrez, Stan Matwin, Johanne Morin, Robert L. Probert: An Application of Explanation-Based Learning to Protocol Conformance Testing. IEEE Expert 5(5): 45-60 (1990)

Patrick Constant, Stan Matwin, Franz Oppacher: LEW: Learning by Watching. IEEE Trans. Pattern Anal. Mach. Intell. 12(3): 294-308 (1990)

Jean Genest, Stan Matwin, Boris Plante: Explanation-Based Learning with Incomplete Theories: A Three-step Approach. ML 1990: 286-294

Stan Matwin, Franz Oppacher, Patrick Constant: Knowledge acquisition by incremental learning from problem-solution pairs. Computational Intelligence 5: 58-66 (1989)

Stan Matwin, Johanne Morin: Learning Procedural Knowledge in the EBG Context. ML 1989: 197-199

Stan Matwin, Stan Szpakowicz, Zbig Koperczak: NEGOPLAN: An Inference-Based Negotiation Support Tool. IFIP Congress 1989: 679-685

Francesco Bergadano, Stan Matwin, Ryszard S. Michalski, Jianping Zhang: Measuring Quality of Concept Descriptions. EWSL 1988: 1-14

Francesco Bergadano, Stan Matwin, Ryszard S. Michalski, Jianping Zhang: Representing and Acquiring Imprecise and Context-dependent Concepts in Knowledge-Based Systems. ISMIS 1988: 270-280

Stan Matwin, Franz Oppacher: Learning by Watching: An Incremental Machine Learning Method that Acquires Rules by Conceptual Clustering. ISMIS 1988: 363-373

Stan Matwin, Stan Szpakowicz, Gregory E. Kersten, Wojtek Michalowski, Zbig Koperczak: A Logic-Based Tools for Negotiation Support. SLP 1987: 499-506

Kenneth Forsythe, Stan Matwin: Copying of Dynamic Structures in a Pascal Environment. Softw., Pract. Exper. 16(4): 335-340 (1986)

Stan Matwin, Tomasz Pietrzykowski: Prograph: A Preliminary Report. Comput. Lang. 10(2): 91-126 (1985)

Douglas R. Skuce, Stan Matwin, Branka Tauzovich, Franz Oppacher, Stan Szpakowicz: A Logic-Based Knowledge Source System for Natural Language Document. Data Knowl. Eng. 1(3): 201-231 (1985)

Stan Matwin, Tomasz Pietrzykowski: Intelligent Backtracking in Plan-Based Deduction. IEEE Trans. Pattern Anal. Mach. Intell. 7(6): 682-692 (1985)

Kenneth Forsythe, Stan Matwin: Implementation Strategies for Plan-Based Deduction. CADE 1984: 426-444

Tomasz Pietrzykowski, Stan Matwin: Exponential Improvement of Efficient Backtracking: A Strategy for Plan-Based Deduction. CADE 1982: 223-239

Stan Matwin, Tomasz Pietrzykowski: Exponential Improvement of Efficient Backtracking: data Structure and Implementation. CADE 1982: 240-259

Stan Matwin: On the Completeness of a Set of Transformations Optimizing Linear Programs. Inf. Process. Lett. 6(5): 165-167 (1977)

Stan Matwin: An Experimental Investigation of Geschke's Method of Global Program Optimization. Inf. Process. Lett. 6(6): 177-179 (1977)