Stochastic Modeling/Machine Learning Publications of Kenneth Paul Baclawski

1. K. Baclawski, M. Cerasoli and G.-C. Rota. Introduction to Probability and Random Processes. Unione Matematica Italiana, Bologna, Italy. (1984)

2. K. Baclawski. An algorithm for generating random accesses. Northeastern University, College of Computer Science. (1988)

3. K. Baclawski. A stochastic model of data access and communication. Advan. in Applied Math. 10:175-200. (1989)

4. K. Baclawski, S. Contractor and R. Wilmot. File access patterns: self-similarity and time evolution. NU-CCS-89-19. Northeastern University, College of Computer Science. (1989)

5. K. Baclawski. An algorithm for generating random accesses. Northeastern University, College of Computer Science. (1990)

6. K. Baclawski. An algorithm for generating random accesses. Northeastern University, College of Computer Science. (1992)

7. K. Alexander, K. Baclawski and G.-C. Rota. A stochastic interpretation of the Riemann Zeta function. Proc. Nat. Acad. Sci. 90:697-699. (January 1993) [pdf]

8. K. Baclawski. TPET: A TP systems emulation tool. Northeastern University, College of Computer Science. (1992)

9. K. Baclawski and J.E. Smith. KEYNET: Fast indexing for semantically rich information retrieval. NU-CCS-94-06. Northeastern University, College of Computer Science. (1994) [pdf]

10. J. Gray, P. Sundaresan, S. Englert, K. Baclawski and P. Weinberger. Algorithms for quickly generating very large synthetic databases. Digital Equipment Corporation. (1993)

11. J. Gray, P. Sundaresan, S. Englert, K. Baclawski and P. Weinberger. Quickly generating billion record synthetic databases. In Proc. ACM SIGMOD Conference 243-252. (1994) [pdf]

12. K. Baclawski. Distributed Computer Database System And Method. United States Patent and Trademark Office. (December 2, 1997) [pdf]

13. K. Baclawski. Distributed Computer Database System And Method Employing Intelligent Agents. United States Patent and Trademark Office. (February 20, 2001) [pdf]

14. K. Baclawski. Search System And Method Based On Multiple Ontologies-B1. United States Patent and Trademark Office. (July 23, 2002) [pdf]

15. K. Baclawski. Distributed Computer Database System And Method For Performing Object Search. United States Patent and Trademark Office. (October 8, 2002) [pdf]

16. K. Baclawski. Knowledge Extraction System And Method. United States Patent and Trademark Office. (October 22, 2002) [pdf]

17. K. Baclawski and T. Niu. Ontologies for Bioinformatics. MIT Press, Cambridge, MA. (October 2005) [ONTOBIO Website]

18. K. Baclawski. Distributed Computer Database System And Method Employing Hypertext Linkage Analysis. United States Patent and Trademark Office. (January 7, 2003) [pdf]

19. K. Baclawski. Distributed Computer Database System And Method Employing Intelligent Agents. United States Patent and Trademark Office. (March 18, 2003) [pdf]

20. K. Baclawski. Classification Of Information Sources Using Graph Structures. United States Patent and Trademark Office. (July 22, 2003) [pdf]

21. K. Baclawski. Bayesian network development. In International Workshop on Software Methodologies, Tools and Techniques 18-48. (September 2004) [pdf][ppt][links]

22. K. Baclawski. The Bayesian Web. The Harvard Medical School. (2004) [pdf]

23. K. Baclawski. Knowledge Extraction System and Method. The United Kingdom Patent Office. (September 7, 2004) [pdf]

24. K. Baclawski. Classification Of Information Sources Using Graphic Structures. United States Patent and Trademark Office. (August 3, 2004) [pdf]

25. K. Baclawski. Information Retrieval Apparatus for Processing a Query for Retrieval of Information from a Database. The United Kingdom Patent Office. (November 2, 2004) [pdf]

26. K. Baclawski. Probabilistic foundations of meta-analysis. Talk at the Harvard School of Public Health . (March 4, 2005) [pdf][ppt]

27. K. Baclawski. The Bayesian Web: Adding Reasoning with Uncertainty to the Semantic Web. Bio-IT Conference . (April 4, 2006) [pdf][ppt][Website]

28. K. Baclawski. Probability and the Web. In Probability Panel. Ontolog Forum. (March 29, 2007) [pdf][ppt][Meeting page]

29. K. Baclawski. Introduction to Probability with R. CRC Press. (January 23, 2008)

30. K. Baclawski and T. Niu. Bioinformatics. Jaico Publishing, Mumbai, India. (2007)

31. K. Baclawski. Search System and Method Based on Multiple Ontologies. European Patent Office. (February 14, 2007)

32. K. Baclawski. Solutions Manual for Introduction to Probability with R. CRC Press. (June 2008)

33. K. Baclawski. Introduction to Probability with R website. Website (2008)

34. K. Baclawski. Situation Awareness and Decision Making. (February 12, 2015) [pdf]

35. K. Baclawski. Applications of Self-Awareness, Situation Awareness and Feedback Control. College of Computer and Information Science, Northeastern University. (May 19, 2015) [pdf]

36. K. Baclawski, E.S. Chan, D. Gawlick, A. Ghoneimy, K. Gross, Z.H. Liu and X. Zhang. Framework for Ontology-Driven Decision Making. Applied Ontology 12(3-4):245-273. IOS Press, The Netherlands. https://bit.ly/2LYPszt (2017) [pdf]

37. K. Baclawski, K. Gross, E.S. Chan, D. Gawlick, A. Ghoneimy and Z.H. Liu. Self-Adaptive Dynamic Decision Making Processes. In IEEE Conference on Cognitive and Computational Aspects of Situation Management . http://bit.ly/2fOG9G2 (2017) [pdf]

38. K. Gross, K. Baclawski, E.S. Chan, D. Gawlick, A. Ghoneimy and Z.H. Liu. A Supervisory Control Loop with Prognostics for Human-in-the-Loop Decision Support and Control Applications. In IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA 2017) . http://bit.ly/2fPlG45 (2017) [pdf]

39. K. Baclawski. Toward Combining Ontologies and Machine Learning for Improving Decision Making. In Ontology Summit 2017: AI, Learning, Reasoning, and Ontologies. http://bit.ly/2DVUS9D (March 15, 2017) [pdf][links]

40. K. Baclawski. The observer effect. In IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA 2018) . (June 11-14, 2018) [pdf]

41. K. Baclawski. A probabilistic time reversal theorem. In IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA 2018) . (June 11-14, 2018) [pdf]

42. K. Baclawski, M. Bennett, G. Berg-Cross, D. Fritzsche, R. Sharma, J. Singer, J. Sowa, R.D. Sriram, M. Underwood and D. Whitten. Ontology Summit 2019: Structure and Discourse. http://bit.ly/2WTduUB (1990) [links]

43. E. Wetherbee, K. Baclawski, G. Wang, K. Gross, A. Chystiakova, D. Gawlick, Z. Liu and P. Sonderegger. System and Method for Ensuring that the Results of Machine Learning Models can be Audited. United States Patent and Trademark Office. (April 2, 2024) [pdf]

44. M. Liu, P. Sonderegger, K. Baclawski, D. Gawlick, A. Chystiakova, G. Wang, Z.H. Liu, H. Balasubramanian and K.C. Gross. Optimizing a Prognostic-Surveillance System to Achieve a User-Selectable Functional Objective. United States Patent and Trademark Office. (February 2, 2023) [pdf]

45. J. Courtney, K. Baclawski, D. Gawlick, K.C. Gross, G. Wang, A. Chystiakova, P. Sonderegger and Z.H. Liu. Machine Learning Traceback-Enabled Decision Rationales as Models for Explainability. United States Patent and Trademark Office. (July 28, 2022) [pdf]

46. J. Rohrkemper, P. Sonderegger, A. Chystiakova, K. Baclawski, D. Gawlick, K.C. Gross, Z. Liu and G. Wang. Root Cause Analysis for Deterministic Machine Learning Model. United States Patent and Trademark Office. (March 2, 2023) [pdf]

47. J. Rohrkemper, K. Baclawski, D. Gawlick, K.C. Gross, G. Wang, A. Chystiakova, P. Sonderegger and Z. Liu. Recommendation Generation Using Machine Learning Data Validation. United States Patent and Trademark Office. (May 18, 2023) [pdf]

48. P. Sonderegger, K. Baclawski, G. Wang, A. Chystiakova, D. Gawlick, Z.H. Liu and K.C. Gross. Automatically adapting a prognostic-surveillance system to account for age-related changes in monitored assets. United States Patent and Trademark Office. (October 10, 2023) [pdf]

49. K. Baclawski, D. Gawlick, K.C. Gross and Z.H. Liu. Prognostic-Surveillance Technique that Dynamically Adapts to Evolving Characteristics of a Monitored Asset. United States Patent and Trademark Office. (October 24, 2023) [pdf]

50. M. Gerdes, K. Baclawski, D. Gawlick, K.C. Gross, G. Wang, A. Chystiakova, P. Sonderegger and Z.H. Liu. Dependency Checking for Machine Learning Models. United States Patent and Trademark Office. (November 23, 2023) [pdf]

51. K. Ru, K. Baclawski, P. Sonderegger, D. Gawlick, A. Chystiakova, G. Wang, M. Gerdes and K.C. Gross. Bias Detection in Machine Learning Tools. United States Patent and Trademark Office. (August 1, 2024) [pdf]