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Computational Health Science

  1. Weller, O., Sagers, L., Hanson, C., Barnes, M., Snell, Q., and Tass, E.S. (2021). Predicting Suicidal Thoughts and Behavior among Adolescents Using the Risk and Protective Factor Framework: A Large-scale Machine Learning Approach. Plos one, 16(11), e0258535.
  2. Jensen, C.D., Duraccio, K.M., Barnett, K.A., Fortuna, C., Woolford, S.J. and Giraud-Carrier, C.G. (2019). Feasibility, Acceptability, and Preliminary Effectiveness of an Adaptive Text Messaging Intervention for Adolescent Weight Control in Primary Care. Clinical Practice in Pediatric Psychology, 7(1):57-67.
  3. Barnes, M., Hanson, C. and Giraud-Carrier, C. (2018). The Case for Computational Health Science. Journal of Health Informatics Research, 2(1):99-110. [PMID: 29974076]
  4. Simms, T., Ramstedt, C., Rich, M., Richards, M., Martinez, T. and Giraud-Carrier, C. (2017). Detecting Cognitive Distortions Through Machine Learning Text Analytics. In Proceedings of the IEEE International Conference on Healthcare Informatics, 508-512.
  5. Chary, M., Genes, N., Giraud-Carrier, C., Hanson, C., Nelson, L.S. and Manini, A.F. (2017). Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media. Journal of Medical Toxicology, 13(4):278-286. [PMID: 28831738]
  6. Braithwaite, S.R., Giraud-Carrier, C., West, J., Barnes, M.D. and Hanson, C.L. (2016). Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality. JMIR Mental Health, 3(2):e21. [PMID: 27185366]
  7. Fortuna, C., Giraud-Carrier, C. and West, J. (2016). Hand-to-Mouth Motion Tracking in Free-Living Conditions for Improved Weight Control. In Proceedings of the IEEE International Conference on Healthcare Informatics, 341-348.
  8. Seaman, I. and Giraud-Carrier, C. (2016). Prevalence and Attitudes About Illicit and Prescription Drugs on Twitter. In Proceedings of the IEEE International Conference on Healthcare Informatics, 14-17.
  9. Chary, M., Genes, N., Giraud-Carrier, C., Hanson, C., Nelson, L., and Manini, A.F. (2015). Estimating nonmedical use of prescription opioids in the United States from social media. Short oral and poster presentation at European Association of Poison Centres and Clinical Toxicologists Annual Congress, Malta. (abstract published in Clinical Toxicology).
  10. Smiley, S., Nielsen, J., Gurgel, R., Zielinski, B., Wright, B., Wang, A., Auduong, P., Foster, N., Giraud-Carrier, C., and Anderson, J. (2014). Validation of quantitative regional atrophy dementia classification in a large clinical MRI sample. Poster at the Organization for Human Brain Mapping (OHBM) Annual Meeting, #1119. Available online at ww4.aievolution.com/hbm1401.
  11. Jashinsky, J., Burton, S.H., Hanson, C.L., West, J., Giraud-Carrier, C., Barnes, M.D. and Argyle, T. (2014). Tracking Suicide Risk Factors Through Twitter in the US. Crisis: The Journal of Crisis Intervention and Suicide Prevention, 35(1):50-59.
  12. Seeley, M., Clement, M., Giraud-Carrier, C., Snell, Q., Bodily, P., Fujimoto, S., Kauwe, J. and Ridge, P.G. (2014) A Structured Approach to Ensemble Learning for Alzheimer's Disease Prediction. In Proceedings of the Fifth ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 605-606.
  13. Thackeray, R., Burton, S.H., Giraud-Carrier, C., Rollins, S. and Draper, C.R. (2013). Using Twitter for Breast Cancer Prevention: An Analysis of Breast Cancer Awareness Month. BMC Cancer, 13:508.
  14. Hanson, C.L., Cannon, B., Burton, S. and Giraud-Carrier, C. (2013). An Exploration of Social Circles and Prescription Drug Abuse through Twitter. Journal of Medical Internet Research, 15(9):e189. [PMID: 24014109]
  15. Hanson, C.L., Burton, S.H., Giraud-Carrier, C., West, J.H., Barnes, M.D. and Hansen, B. (2013). Tweaking and Tweeting: Exploring Twitter for Nonmedical Use of a Psychostimulant Drug (Adderall) Among College Students. Journal of Medical Internet Research, 15(4):e62. [PMID: 23594933]
  16. Lee, J. and Giraud-Carrier, C. (2013). Results on Mining NHANES Data: A Case Study in Evidence-based Medicine. Computers in Biology and Medicine, 43(5):493-503.
  17. Neiger, B.L., Thackeray, R., Burton, S.H., Giraud-Carrier, C. and Fagen, M.C. (2013). Evaluating Social Media's Capacity to Develop Engaged Audiences in Health Promotion Settings: Use of Twitter Metrics as a Case Study. Health Promotion Practice, 14(2):157-162.
  18. Burton, S.H., Tew, C.V., Cueva, S.S., Giraud-Carrier, C.G. and Thackeray, R. (2013). Social Moms and Health: A Multi-platform Analysis of Mommy Communities. In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 169-174.
  19. Burton, S.H., Tanner, K.W., Giraud-Carrier, C.G., West, J.H. and Barnes, M.D. (2012). “Right Time, Right Place“ Health Communication on Twitter: Value and Accuracy of Location Information. Journal of Medical Internet Research, 14(6):e156. [PMID: 23154246]
  20. Burton, S., Tanner, K. and Giraud-Carrier, C. (2012). Leveraging Social Networks for Anytime-Anyplace Health Information. Journal of Network Modeling Analysis in Health Informatics and Bioinformatics, 1(4):173-181.
  21. West, J.H., Hall, P.C., Hanson, C.L., Barnes, M.D., Giraud-Carrier, C. and Barrett, J.S. (2012). There's An App for That: Content Analysis of Paid Health & Fitness Apps. Journal of Medical Internet Research, 14(3):e72. [PMID: 22584372]
  22. West, J.H., Hall, P.C., Prier, K., Hanson, C.L., Giraud-Carrier, C., Neeley, E.S. and Barnes, M.D. (2012). Temporal Variability of Problem Drinking on Twitter. Open Journal of Preventive Medicine, 2(1):43-48.
  23. Burton, S., Morris, R., Hansen, J., Dimond, M., Giraud-Carrier, C., West, J., Hanson, C. and Barnes, M. (2012). Public Health Community Mining in YouTube. In Proceedings of the Second International Health Informatics Symposium, 81-90.
  24. Prier, K.W., Smith, M.S., Giraud-Carrier, C. and Hanson, C.L. (2011). Identifying Health-Related Topics in Twitter : An Exploration of Tobacco-Related Tweets as a Test Topic. In Proceedings of the Fourth International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, 18-25.
  25. Giraud-Carrier, C., Pixton, B. and Rocha, R. (2009). Bariatric Surgery Performance: An Observational Study Using Data Mining Techniques. Journal of Intelligent Data Analysis, 13(5):741-754.
  26. Giraud-Carrier, C. (2008). Improving Clinical Research with Predictive Informatics. Poster at the AMIA Clinical Research Informatics Working Group Expo.
  27. Langford, T., Giraud-Carrier, C. and Magee, J. (2001). Detection of Infectious Outbreaks in Hospitals through Incremental Clustering. In AIME 2001 (Proceedings of the Eighth European Conference on Artificial Intelligence in Medicine), S. Quaglini, P. Barahona and S. Andreassen (Eds.), LNAI 2101, 30-39.

Metalearning / AutoML

  1. Johnson, J. and Giraud-Carrier, C. (2019). Diversity, Accuracy and Efficiency in Ensemble Learning: An Unexpected Result. Intelligent Data Analysis, 23(2):297-311.
  2. Brazdil, P. and Giraud-Carrier, C. (2018). Metalearning and Algorithm Selection: Progress, State of the Art and Introduction to the 2018 Special Issue. Machine Learning, 107(1):1-14.
  3. Schoenfeld, B., Giraud-Carrier, C., Poggemann, M., Christensen, J. and Seppi, K. (2018). Preprocessor Selection for Machine Learning Pipelines. In Proceedings of the AutoML 2018 Workshop at the Thirty-fifth International Conference on Machine Learning.
  4. Davis, C. and Giraud-Carrier, C. (2018). Annotative Experts for Hyperparameter Selection. In Proceedings of the AutoML 2018 Workshop at the Thirty-fifth International Conference on Machine Learning.
  5. Brazdil, P., Vilalta, R., Giraud-Carrier, C. and Soares, C. (2017). Metalearning. In Sammut, C. and Webb, G.I. (Eds.), Encyclopedia of Machine Learning, 2nd Edition, 818-823.
  6. Sanders, S. and Giraud-Carrier, C. (2017). Informing the Use of Hyperparameter Optimization Through Metalearning. In Proceedings of the IEEE International Conference on Data Mining, 1051-1056.
  7. 58. Smith, M.R., Martinez, T. and Giraud-Carrier, C. (2015). The Potential Benefits of Data Set Filtering and Learning Algorithm Hyperparameter Optimization. In Proceedings of the ECML Workshop on Meta-Learning and Algorithm Selection, CEUR 1455, 3-14.
  8. Smith, M.R., Martinez, T. and Giraud-Carrier, C. (2014). An Instance Level Analysis of Data Complexity. Machine Learning, 95(2):225-256.
  9. Lee, J. and Giraud-Carrier, C. (2014). On the Dangers of Default Implementations: The Case of Radial Basis Function Networks. Intelligent Data Analysis, 18(2):261-279.
  10. Ridd, P. and Giraud-Carrier, C. (2014). Using Metalearning to Predict When Parameter Optimization Is Likely to Improve Classification Accuracy. In Proceedings of the ECAI Workshop on Meta-Learning and Algorithm Selection, CEUR 1201, 18-23.
  11. Smith, M., Mitchell, L., Giraud-Carrier, C. and Martinez, T. (2014). Recommending Learning Algorithms and Their Associated Hyperparameters. In Proceedings of the ECAI Workshop on Meta-Learning and Algorithm Selection, CEUR 1201, 39-40.
  12. Smith, M., White, A., Giraud-Carrier, C. and Martinez, T. (2014). An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. In Proceedings of the ECAI Workshop on Meta-Learning and Algorithm Selection, CEUR 1201, 41-48.
  13. Lee, J. and Giraud-Carrier, C. (2013). Automatic Selection of Classification Learning Algorithms for Data Mining Practitioners. Intelligent Data Analysis, 17(4):665-678.
  14. Brazdil, P., Vilalta, R., Soares, C. and Giraud-Carrier, C. (2012). Metalearning. In Seel, N.M. (Ed.), Encyclopedia of the Sciences of Learning, 762.
  15. Lee, J. and Giraud-Carrier, C. (2011). A Metric for Unsupervised Metalearning. Intelligent Data Analysis, 15(6):827-841.
  16. Brazdil, P., Vilalta, R., Giraud-Carrier, C. and Soares, C. (2010). Metalearning. In Sammut, C. and Webb, G.I. (Eds.), Encyclopedia of Machine Learning, 662-666.
  17. Brazdil, P., Giraud-Carrier, C., Soares, C., and Vilalta, R. (2009). Metalearning: Applications to Data Mining. Springer.
  18. Lee, J. and Giraud-Carrier, C. (2008). New Insights Into Learning Algorithms and Datasets. In Proceedings of the Seventh International Conference on Machine Learning and Applications, 135-140.
  19. Lee, J. and Giraud-Carrier, C. (2008). Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features. In Proceedings of the Seventh International Conference on Machine Learning and Applications, 808-812.
  20. Gashler, M., Giraud-Carrier, C. and Martinez, T. (2008). Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous. In Proceedings of the Seventh International Conference on Machine Learning and Applications, 900-905.
  21. Giraud-Carrier, C., Brazdil, P., Soares, C. and Vilalta, R. (2008). Meta-learning. In Wang, J. (Ed.), Encyclopedia of Data Warehousing and Mining, 2nd Edition, 1207-1215.
  22. Giraud-Carrier, C. and Provost, F. (2005). Toward a Justification of Meta-learning: Is the No Free Lunch Theorem a Show-stopper? In Proceedings of the ICML-2005 Workshop on Meta-learning, 12-19.
  23. Giraud-Carrier, C. (2005). The Data Mining Advisor: Meta-learning at the Service of Practitioners. In Proceedings of the Fourth International Conference on Machine Learning and Applications, 113-119.
  24. Vilalta, R., Giraud-Carrier, C. and Brazdil, P. (2005). Meta-learning. In Maimon, O. and Rokach, L. (Eds.), Data Mining and Knowledge Discovery Handbook, Springer, 731-748.
  25. Giraud-Carrier, C., Vilalta, R. and Brazdil, P. (2004). Introduction to the Special Issue on Meta-learning. Machine Learning, 54(3):187-193.
  26. Vilalta, R., Giraud-Carrier, C., Brazdil, P. and Soares, C. (2004). Using Meta-Learning to Support Data-Mining. International Journal of Computer Science and Applications, Vol. I, No. 1, 31-45.
  27. Giraud-Carrier, C. and Keller, J. (2002). Meta-learning. In Meij, J. (Ed.), Dealing with the Data Flood: Mining Data, text and Multimedia. STT 65, STT/Beweton, The Hague, 832-844.
  28. Pfahringer, B., Bensusan, H. and Giraud-Carrier, C. (2000). Meta-learning by Landmarking Various Learning Algorithms. In Proceedings of the Seventeenth International Conference on Machine Learning, 743-750.
  29. Bensusan, H. and Giraud-Carrier, C. (2000). Harmonia Loosely Praestabilita: Discovering Adequate Inductive Strategies. In Proceedings of the Twenty Second Annual Meeting of the Cognitive Science Society (CogSci2000), 609-614.
  30. Bensusan, H. and Giraud-Carrier, C. (2000). Discovering Task Neighbourhoods through Landmark Learning Performances. In Proceedings of the Fourth European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD-2000), LNAI 1910, 325-330.
  31. Bensusan, H., Giraud-Carrier, C., Pfahringer, B., Soares, C. and Brazdil, P. (2000). What Works Well Tells Us What Works Better. In Proceedings of the ICML-2000 Workshop on What Works Well Where, 1-8 (invited contribution).
  32. Bensusan, H. and Giraud-Carrier, C. (2000). Casa Batló is in Passeig de Gràcia or Landmarking the Expertise Space. In Proceedings of the ECML-2000 Workshop on Meta-learning: Building Automatic Advice Strategies for Model Selection and Method Combination, 29-46.
  33. Bensusan, H., Giraud-Carrier, C. and Kennedy, C. (2000). A Higher-order Approach to Meta-learning. In Proceedings of the ECML-2000 Workshop on Meta-learning: Building Automatic Advice Strategies for Model Selection and Method Combination, 109-118.
  34. Giraud-Carrier, C. (1998). Beyond Predictive Accuracy: What? In ECML'98 Workshop Notes - Upgrading Learning to the Meta-Level: Model Selection and Data Transformation, 78-85.

Machine Learning and Data Mining

  1. Sharma, R., Chelladurai, I., Orme, A.D., Miles, M.P., Giraud-Carrier, C. and Fullwood, D.T. (2018). A Step Towards Intelligent EBSD Microscopy: Machine-learning Prediction of Twin Activity in MgAZ31. Journal of Microscopy, 272(1):67-78.
  2. Orme, A.D., Fullwood, D.T., Miles, M.P. and Giraud-Carrier, C. (2018). Evolution of MgAZ31 Twin Activation with Strain: A Machine Learning Study. Materials Discovery, 12:20-29.
  3. Gustafson, N. and Giraud-Carrier, C. (2014). A Confidence-Prioritization Approach for Learning Noisy Data. International Journal of Data Analysis Techniques and Strategies, 6(4):307-326.
  4. Burton, S.H, Morris, R.G., Giraud-Carrier, C.G., West, J.H. and Thackeray, R. (2014). Mining Useful Association Rules from Questionnaire Data. Intelligent Data Analysis, 18(3):479-494.
  5. Tew, C., Giraud-Carrier, C., Burton, S. and Tanner, K. (2014). Behavior-based Clustering and Analysis of Interestingness Measures for Association Rule Mining. Data Mining and Knowledge Discovery, 28(4):1004-1045.
  6. Tanner, K., Giraud-Carrier, C. and Olsen, D.O. (2014). Formatting by Demonstration: An Interactive Machine Learning Approach. International Journal of Computer Applications, 86(18):41-47.
  7. Taylor, Q. and Giraud-Carrier, C. (2010). Applications of Data Mining in Software Engineering. International Journal of Data Analysis Techniques and Strategies, 2(3):243-257.
  8. Heath, D., Zitzelberger, A. and Giraud-Carrier, C. (2010). A Multiple Domain Comparison of Multi-label Classification Methods. In Working Notes of the 2nd ICML International Workshop on Learning from Multi-Label Data, 21-28.
  9. Oviatt, D., Frandsen, D., Clements, K. and Giraud-Carrier, C. (2008). An Instance-based Nearest-neighbor Approach to Classifying Nuclear Explosion Data. In Summary Booklet of the Data Mining Contest at the IEEE International Conference on Data Mining, 12-15.
  10. Giraud-Carrier (2008). Data Mining Tool Selection. In Wang, J. (Ed.), Encyclopedia of Data Warehousing and Mining, 2nd Edition, 511-518.
  11. Giraud-Carrier, C. and Smith, M. (2008). Web Mining: Stages of Knowledge Discovery in e-Commerce Sites. In Wang, J. (Ed.), Encyclopedia of Data Warehousing and Mining, 2nd Edition, 1830-1834.
  12. Giraud-Carrier, C. and Martinez, T. (2007). Learning by Discrimination: A Constructive Incremental Approach. Journal of Computers, 2(7):49-58.
  13. Lee, J. and Giraud-Carrier, C. (2007). Transfer Learning in Decision Trees. In Proceedings of the International Joint Conference on Neural Networks, 726-731.
  14. Ivie, S., Pixton, B. and Giraud-Carrier, C. (2007). Metric-Based Data Mining Model for Genealogical Record Linkage. In Proceedings of the IEEE International Conference on Information Reuse and Integration, 538-543.
  15. Smith, M., Wenerstrom, B., Giraud-Carrier, C., Lawyer, S. and Liu, W. (2007). Personalizing e-Commerce with Data Mining. In E-Service Intelligence: Methodologies, Technologies and Applications, Lu, J., Ruan, D. and Zhang, G. (Eds.), Studies in Computational Intelligence Series, Vol. 37, Springer, Chapter 12. [Extended version of ESI/JCIS 2005 paper].
  16. Ivie, S., Henry, G., Gatrell, H. and Giraud-Carrier, C. (2007). A Metric-Based Machine Learning Approach to Genealogical Record Linkage. In Proceedings of the 7th Annual Workshop on Technology for Family History and Genealogical Research.
  17. Wenerstrom, B. and Giraud-Carrier, C. (2006). Temporal Data Mining in Dynamic Feature Spaces. In Proceedings of the Sixth International Conference on Data Mining, 1141-1145.
  18. Daniels, K. and Giraud-Carrier, C. (2006). Learning the Threshold in Hierarchical Agglomerative Clustering. In Proceedings of the Fifth International Conference on Machine Learning and Applications, 270-275.
  19. Giraud-Carrier, C. and Martinez, T. (2006). A Constructive Incremental Learning Algorithm for Binary Classification Tasks. In Proceedings of the IEEE Mountain Workshop on Adaptive and Learning Systems, 213-218.
  20. Pixton, B. and Giraud-Carrier, C. (2006). Using Structured Neural Networks for Record Linkage. In Proceedings of the 6th Annual Workshop on Technology for Family History and Genealogical Research.
  21. 86. Giraud-Carrier, C. and Ventura, D. (2005). Effecting Transfer via Learning Curve Analysis. NIPS Workshop on Inductive Transfer: 10 Years Later.
  22. Pixton, B. and Giraud-Carrier, C. (2005). MAL4:6 - Using Data Mining for Record Linkage. In Proceedings of the 5th Annual Workshop on Technology for Family History and Genealogical Research.
  23. Povel, O. and Giraud-Carrier, C. (2004). SwissAnalyst: Data Mining without the Entry Ticket. In Bramer, M. and Devedzic, V. (Eds.), Artificial Intelligence Applications and Innovations (IFIP 18th World Computer Congress, TC12 First International Conference on Artificial Intelligence Applications and Innovations AIAI-2004), Kluwer, 393-406.
  24. Giraud-Carrier, C. and Povel, O. (2003). Characterising Data Mining Software. Journal of Intelligent Data Analysis, 7(3):181-192.
  25. Giraud-Carrier, C. (2002). Unifying Learning and Evolution Through Baldwinian Evolution and Lamarckism: A Case Study. In Zimmermann, H-J., Tselentis, G., van Someren, M. and Dounias, G. (Eds.), Advances in Computational Intelligence and Learning: Methods and Applications. The Kluwer International Series in Intelligent Technologies, Vol. 18, 159-168. [Extended version of CoIL 2000 paper].
  26. Giraud-Carrier, C. and Kennedy, C.J. (2001). ADFs: An Evolutionary Approach to Predicate Invention. In Proceedings of the Fifth International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA'01), 224-227.
  27. Giraud-Carrier, C. (2000). A Note on the Utility of Incremental Learning. AI Communications, 13(4):215-223.
  28. Bogacz, R., and Giraud-Carrier, C. (2000). A Novel Modular Neural Architecture for Rule-based and Similarity-based Reasoning. In Wermter, S. and Sun, R. (Eds.), Hybrid Neural Systems, LNAI 1778, Springer-Verlag, 63-77.
  29. Giraud-Carrier, C., Corley, S. and Dattani, I. (1999). Case Base Management Through Induction. In Proceedings of the IJCAI'99 Workshop on Automating the Construction of Case-based Reasoners, 44-49.
  30. Lock, D. and Giraud-Carrier, C. (1999). Evolutionary Programming of Near-Optimal Neural Networks. In Proceedings of the Fourth International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA'99), 302-306.
  31. Bogacz, R., and Giraud-Carrier, C. (1998). Learning Meta-Rules of Selection in Expert Systems. In Proceedings of the Fourth World Congress on Expert Systems (WCES'98), Vol. 2, 576-581.
  32. Giraud-Carrier, C., and Corley, S. (1998). Inductive CBR for Customer Support. In Proceedings of the Second International Conference on the Practical Application of Knowledge Discovery and Data Mining (PADD'98), 131-141.
  33. Giraud-Carrier, C., and Ward, M. (1997). Learning Customer Profiles to Generate Cash over the Internet. In Proceedings of the Third International Workshop on Applications of Neural Networks to Telecommunications (IWANNT'97), 165-170.
  34. Burdsall, B., and Giraud-Carrier, C. (1997). GA-RBF: A Self-Optimising RBF Network. In Proceedings of the Third International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA'97). 346-349.
  35. Burdsall, B., and Giraud-Carrier, C. (1997). Evolving Fuzzy Prototypes for Efficient Data Clustering. In Proceedings of the Second International ICSC Symposium on Fuzzy Logic and Applications (ISFL'97), 217-223.
  36. Bogacz, R. and Giraud-Carrier, C. (1997). Supervised Competitive Learning for Finding Positions of Radial Basis Functions. In Proceedings of the Third Polish Conference on Neural Networks and Applications, 701-706.
  37. Giraud-Carrier, C. (1996). FLARE: Induction with Prior Knowledge. In Nealon, J.L. and Hunt, J. (Eds.), Research and Development in Expert Systems XIII (Proceedings of Expert Systems'96), SGES Publications, 11-24. Best Technical Paper Award.
  38. Giraud-Carrier, C., and Martinez, T. (1995). AA1*: A Dynamic Incremental Network that Learns by Discrimination. In Proceedings of the Second International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA'95), 45-48.
  39. Giraud-Carrier, C., and Martinez, T. (1995). An Efficient Metric for Heterogeneous Inductive Learning Applications in the Attribute-Value Language. Intelligent Systems (Proceedings of GWIC'94), E.A. Yfantis (Ed.), Kluwer Academic Publishers, Vol. 1, 341-350.
  40. Giraud-Carrier, C., and Martinez, T. (1995). An Integrated Framework for Learning and Reasoning. Journal of Artificial Intelligence Research, 3:147-185.
  41. Giraud-Carrier, C., and Martinez, T. (1995). Analysis of the Convergence and Generalization of AA1. Journal of Parallel and Distributed Computing, 26(1):125-131.
  42. Giraud-Carrier, C., and Martinez, T. (1994). Seven Desirable Properties for Artificial Learning Systems. In Proceedings of the Seventh Florida AI Research Symposium (FLAIRS'94), 16-20.
  43. Giraud-Carrier, C., and Martinez, T. (1994). An Incremental Learning Model for Commonsense Reasoning. In Proceedings of the Seventh International Symposium on Artificial Intelligence (ISAI'94), 134-141.
  44. Giraud-Carrier, C., and Martinez, T. (1993). Using Precepts to Augment Training Set Learning. In Proceedings of the First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert systems (ANNES'93), 46-51.
  45. Martinez, T., Barker, C., and Giraud-Carrier, C. (1993). A Generalizing Adaptive Discriminant Network. In Proceedings of the World Congress on Neural Networks (WCNN'93), Vol. I, 613-616.

Structure-rich Machine Learning

  1. Thie, C. and Giraud-Carrier, C. (2005). Learning Concept Descriptions with Typed Evolutionary Programming. IEEE Transactions on Knowledge and Data Engineering, 17(12): 1664-1677.
  2. MacKinney-Romero, R. and Giraud-Carrier, C. (2004). Inducing Classification Rules from Highly-structured Data with Composition. In Proceedings of the Third Mexican International Conference on Artificial Intelligence (MICAI'04), LNAI 2972, 262-271.
  3. Bowers, A., Giraud-Carrier, C. and Lloyd, J.W. (2000). Classification of Individuals with Complex Structure. In Proceedings of the Seventeenth International Conference on Machine Learning, 81-88.
  4. Bensusan, H., Giraud-Carrier, C. and Kennedy, C. (2000). A Higher-order Approach to Meta-learning. In Proceedings of the ILP-2000 Work-in-Progress Track, 33-42.
  5. Kennedy, C.J., Giraud-Carrier, C. and Bristol, D.W. (1999). Predicting Chemical Carcinogenesis Using Structural Information Only. In Proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'99), LNAI 1704, 360-365.
  6. Kennedy, C.J. and Giraud-Carrier, C. (1999). A Depth Controlling Strategy for STEPS. In Proceedings of the 1999 Genetic and Evolutionary Computation Conference (GECCO'99), Vol. 1, 879-885.
  7. MacKinney-Romero, R. and Giraud-Carrier, C. (1999). Learning from Highly Structured Data by Decomposition. In Proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'99), LNAI 1704, 436-441.
  8. Kennedy, C. and Giraud-Carrier, C. (1999). An Evolutionary Approach to Concept Learning with Structured Data. In Proceedings of the Fourth International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA'99), 331-336.
  9. Flach, P.A., Giraud-Carrier, C. and Lloyd, J.W. (1998). Strongly-Typed Inductive Concept Learning. Proceedings of the Eighth International Conference on Inductive Logic Programming, LNAI 1446, 185-194.
  10. Bowers, A.F., Giraud-Carrier, C., Kennedy, C., Lloyd, J.W. and MacKinney-Romero, R. (1997). A Framework for Higher-Order Inductive Machine Learning. In Proceedings of the COMPULOGNet Area Meeting on Representation Issues in Reasoning and Learning, 19-25.

Social Networks and Social Capital

  1. Burton, S.H. and Giraud-Carrier, C. (2014). Discovering Social Circles in Directed Graphs. ACM Transactions on Knowledge Discovery from Data, 8(4):21.
  2. Stirling, W., Giraud-Carrier, C. and Felin, T. (2012). A Framework for the Design and Synthesis of Coordinated Social Systems. In Proceedings of the Fourth International Conference on Social Informatics (LNCS 7710), 351-364.
  3. Smith, M., Giraud-Carrier, C., Dewey, D., Ring, S. and Gore, D. (2011). Social Capital and Language Acquisition during Study Abroad. In Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society, 2030-2035.
  4. Smith, M., Giraud-Carrier, C. and Purser, N. (2009). Implicit Affinity Networks and Social Capital. Journal of Information Technology and Management, 10(2-3):123-134.
  5. Smith, M. and Giraud-Carrier, C. (2010). Bonding vs. Bridging Social Capital: A Case Study in Twitter. In Proceedings of the Second International Symposium on Social Intelligence and Networking, 385-392.
  6. Smith, M., Purser, N. and Giraud-Carrier, C. (2008). Social Capital in the Blogosphere: A Case Study. In Papers from the AAAI Spring Symposium on Social Information Processing, K. Lerman et al. (Eds.), Technical Report SS-08-06, AAAI Press, 93-97.
  7. Smith, M., Giraud-Carrier, C. and Judkins, B. (2007). Implicit Affinity Networks. In Proceedings of the Seventeenth Annual Workshop on Information Technologies and Systems, 1-6.
  8. Smith, M. and Giraud-Carrier, C. (2006). Genealogical Implicit Affinity Networks. In Proceedings of the 6th Annual Workshop on Technology for Family History and Genealogical Research.

Miscellaneous

  1. Cheng, Y., Yuan, Y., Chen, L., Giraud-Carrier, C., Wang, G. and Li, B. (2021). Event-Participant and Incremental Planning over Event-Based Social Networks. IEEE Transactions on Knowledge and Data Engineering, 33(2):474-488.
  2. Qiao, B., Hua, B., Zhu, J., Wu, G., Giraud-Carrier, C. and Wang, G. (2020). A Top-k Spatial Join Querying Processing Algorithm Based on Spark. Information Systems, 87:101419.
  3. Cheng, Y., Yuan, Y., Chen, L., Giraud-Carrier, C. and Wang, G. (2017). Complex Event-Participant Planning and Its Incremental Variant. In Proceedings of the IEEE 33rd International Conference on Data Engineering, 859-871.
  4. Cheng, Y., Yuan, Y., Chen, L., Wang, G., Giraud-Carrier, C. and Sun, Y. (2016). DistR: A Distributed Method for the Reachability Query over Large Uncertain Graphs. IEEE Transactions on Parallel and Distributed Systems, 27(11):3172-3185.
  5. Vaziripour, E., Giraud-Carrier, C. and Zappala, D. (2016). Analyzing the Political Sentiment of Tweets in Farsi. In Proceedings of the Tenth International AAAI Conference on Web and Social Media, 699-702.
  6. Han, D., Giraud-Carrier, C. and Shuoru, L. (2015). Efficient Mining of High-speed Uncertain Data Streams. Applied Intelligence, 43(4):773-785.
  7. Giraud-Carrier, C., Goodliffe, J., Jones, B.M. and Cueva, S. (2015). Effective Record Linkage for Mining Campaign Contribution Data. Knowledge and Information Systems, 45(2):389-416.
  8. Davis, N., Giraud-Carrier, C. and Jensen, D. (2010). A Topological Embedding of the Lexicon for Semantic Distance Computation. Natural Language Engineering, 16(3):245-275.
  9. Hawkins, B. and Giraud-Carrier, C. (2009). Ranking Search Results for Translated Content. In Proceedings of the IEEE International Conference on Information Reuse and Integration, 242-245.
  10. Dinerstein, S., Giraud-Carrier, C., Dinerstein, J. and Egbert, P. (2009). Fused Multi-modal Deduplication. In Proceedings of the International Conference on Data Mining (DMIN'09), 253-259.
  11. Valentine, D., Mortorff, D. and Giraud-Carrier, C. (2009). Implementing a Surname Study Website with Drupal. Journal of One-Name Studies, 10(4):21-23.
  12. Valentine, D., Mortorff, D. and Giraud-Carrier, C. (2009). Implementing a Surname Study Website with Drupal. In Proceedings of the 9th Annual Workshop on Technology for Family History and Genealogical Research, 88-95.
  13. Goodliffe, J., Jones, B., Magleby, D.B., Olsen, J.A., Giraud-Carrier, C. Huang, Y., Rowley, W. and Wilcox, D. (2009). Using Record Linkage to Study Campaign Contributors. Poster at the Political Methodology Conference.
  14. Jensen, D., Giraud-Carrier, C., and Davis, N. (2008). A Method for Computing Lexical Semantic Distance Using Linear Functionals. Journal of Web Semantics: Science, Services and Agents on the World Wide Web, 6:99-108.
  15. Jensen, D. and Giraud-Carrier, C. (2007). A Topological Embedding of the Lexicon for Effective Semantic Distance Computation. In Proceedings of the Seventh International Workshop on Computational Semantics, 259-270.
  16. Delorey, D., Knutson, C. and Giraud-Carrier, C. (2007). Programming Language Trends in Open Source Development: An Evaluation Using Data from All Production Phase SourceForge Projects. In Proceedings of the Second Workshop on Public Data about Software Development.
  17. Tran, N., Giraud-Carrier, C., Seppi, K. and Warnick, S. (2006). Cooperation-based Clustering for Profit-Maximizing Organizational Design. In Proceedings of the International Joint Conference on Neural Networks, 3479-3483.
  18. Tran, N., West, D., Giraud-Carrier, C., Seppi, K., Warnick, S. and Johnson, R. (2005). The Value of Cooperation Within a Profit-Maximizing Organization. In Proceedings of the Fourth International Conference on Computational Intelligence in Economics and Finance at the Eighth Joint Conference on Information Sciences, 1017-1020.
  19. Dahl, T.S. and Giraud-Carrier, C. (2005). Incremental Development of Adaptive Behaviors using Trees of Self-Contained Solutions. Adaptive Behavior, 13(3):243-260.
  20. Fall, C.J. and Giraud-Carrier, C. (2005). Searching Trademark Databases for Verbal Similarities. World Patent Information, 27(2):135-143.
  21. Giraud-Carrier, C., Miclo, P., Daudin, H. and Du Pasquier, J. (2004). An Extranet Waste Inventory Application. In Proceedings of the Eighteenth International Conference on Informatics for Environmental Protection (EnviroInfo Symposium 2004), 37-47.
  22. Dahl, T. and Giraud-Carrier, C. (2004). Evolution-inspired Incremental Development of Complex Autonomous Intelligence. In Proceedings of the Eighth International Conference on Intelligent Autonomous Systems (IAS'04), 395-402.
  23. Bogacz, R., Brown, M.W. and Giraud-Carrier, C. (2001). Model of Familiarity Discrimination in the Perirhinal Cortex. Journal of Computational Neuroscience, 10:5-23.
  24. Bogacz, R., Brown, M.W. and Giraud-Carrier, C. (2001). Emergence of Motion-sensitive Neurons' Properties by Learning Sparse Code for Natural Moving Images. Advances in Neural Information Processing Systems (Proc. of NIPS-2000), 13:838-844.
  25. Dahl, T. and Giraud-Carrier, C. (2001). Evolution, Adaption and Behavioural Holism in Artificial Intelligence. Advances in Artificial Life (Proceedings of the Sixth European Conference, ECAL 2001), J. Kelemen and P. Sosik (Eds.), LNAI 2159, 499-508.
  26. Bogacz, R., Brown, M.W. and Giraud-Carrier, C. (2001). Model of Co-operation between Recency, Familiarity and Novelty Neurons in the Perirhinal Cortex. In Neurocomputing (Proc. of CNS-2000), 38:1121-1126.
  27. Dahl, T. and Giraud-Carrier, C. (2001). PLANCS: Classes for Programming Adaptive Behaviour Based Robots. In Proceedings of the AISB'01 Symposium on Nonconscious Intelligence: From Natural to Artificial, 9-20.
  28. Bogacz, R., Brown, M.W. and Giraud-Carrier, C. (2001). A Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex. In Wermter, S., Austin, J. and Willshaw, D. (Eds.), Emergent Neural Computational Architectures based on Neuroscience. LNAI 2036, 428-441. [Extended version of EmerNet 1999 paper].
  29. Bogacz, R., Brown, M.W. and Giraud-Carrier, C. (2000). Frequency-based Error Backpropagation in a Cortical Network. In Proceedings of the International Joint Conference on Neural Networks, Vol. II, 211-216.
  30. Bogacz, R., Brown, M.W. and Giraud-Carrier, C. (1999). High Capacity Neural Networks for Familiarity Discrimination. In Proceedings of the Ninth International Conference on Artificial Neural Networks (ICANN'99), Vol. 2, 773-778.
  31. Bogacz, R., and Giraud-Carrier, C. (1998). BRAINN: A Connectionist Approach to Symbolic Reasoning. In Proceedings of the First International ICSC/IFAC Symposium on Neural Computation (NC'98), 907-913.
  32. Giraud-Carrier, C. (1994). A Reconfigurable Data Flow Machine for Implementing Functional Programming Languages. SIGPLAN Notices, 29(9):22-28.
  33. Giraud-Carrier, C., Woodfield, S., and Embley, D. (1993). State Nets: An Expressively Efficient Behavioral Model. In Proceedings of the Twelfth Annual IEEE International Phoenix Conference on Computers and Communication (IPCCC'93), 571-577.