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Conference Papers (Refereed)

  1. Yang, H., Aguirre, C. A., De La Torre, M. F., Christensen, D., Bobadilla, L., Davich, E., Roth, J., Luo, L., Theis, Y., Lam, A., Han, T. Y.-J., Buttler, D., & Hsu, W. H. (2019). Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. Proceedings of the 2nd International Conference on Document Analysis and Recognition Workshop on Open Services and Tools for Document Analysis (ICDAR-OST 2019), Sydney, Australia, September 21 2019, to appear.
  2. Behzadan, V. & Hsu, W. (2019). RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies. Proceedings of the 2nd International Workshop on Artificial Intelligence Safety Engineering (WAISE 2019), Turku, Finland, September 10, 2019, to appear.
  3. Behzadan, V. & Hsu, W. (2019). Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Artificial Intelligence Safety (AISafety 2019), Macau, China, August 11, 2019, to appear.
  4. Tanash, M., Dunn, B., Andresen, D., Hsu, W., Yang, H., Okanlawon, A. (2019). Improving HPC System Performance by Predicting Job Resources via Supervised Machine Learning. Proceedings of the 3rd Conference on Practice and Experience in Advanced Research Computing (PEARC 2019), Chicago, IL, USA, July 28 - August 1, 2019, to appear.
  5. Lamba, D., Alsadhan, M., Hsu, W., Fitzsimmons, E., & Newmark, G. (2019). Coping with Class Imbalance in Classification of Traffic Crash Severity Based on Sensor and Road Data: A Feature Selection and Data Augmentation Approach. In Nagamalai, D. et al., eds. Proceedings of the 6th International Conference on Data Mining and Database (DMDB 2019), pp. 125-137, Vancouver, BC, Canada, May 25-26, 2019.
  6. Behzadan, V., Aguirre, C., Bose, A., & Hsu, W. (2018). Corpus and Deep Learning Classifier for Collection of Cyber Threat Indicators in Twitter Stream. Proceedings of the IEEE International Conference on Big Data 2018 (IEEE BigData 2018) Workshop on Big Data Analytics for Cyber Threat Hunting (CyberHunt 2018), Seattle, WA, USA, December 10-13, 2018.
  7. De La Torre, M. F., Aguirre, C. A., Anshutz, B., & Hsu, W. (2018). MATESC: Metadata-Analytic Text Extractor and Section Classifier for Scientific Publications. Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018): International Conference on Knowledge Discovery and Information Retrieval (KDIR 2018), Seville, Spain, September 18-20, 2018.
  8. Yates, H., Chamberlain, B., Healey, J., & Hsu, W. (2018). Binary Classification of Arousal in Built Environments using Machine Learning. Working Notes of the 2nd International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Artificial Intelligence in Affective Computing, Stockholm, Sweden, July 15, 2018.
  9. De La Torre, M. F., Hsu, W., & Cain, M. (2018). PawFriends: Small Vertebrate Motion Tracking and Behavioral Recognition from Video using LSTM. Working Notes of the 2nd International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Cognitive Vision: Integrated Vision and AI for Embodied Perception and Interaction (CogVis 2018), Stockholm, Sweden, July 14, 2018.
  10. Kallumadi, S. & Hsu, W. H. (2018). Interactive Recommendations by Combining User-Item Preferences with Linked Open Data. Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (UMAP 2018), Nanyang Technological University, Singapore, July 8 - 11, 2018.
  11. Andresen, D., Hsu, W., Yang, H., & Okanlawon, A. (2018). Machine Learning for Predictive Analytics of Compute Cluster Jobs. Proceedings of the 16th International Conference on Scientific Computing (CSC 2018), Las Vegas, Nevada, USA, July 30 - August 2, 2018.
  12. Aguirre, C. A., Coen, S., De La Torre, M. F., Hsu, W. H., & Rys, M. (2018). Towards Faster Annotation Interfaces for Learning to Filter in Information Extraction and Search. Proceedings of the 2nd ACM Intelligent User Interfaces (IUI) Workshop on Exploratory Search and Interactive Data Analytics (ESIDA 2018), Tokyo, Japan, March 11, 2018.
  13. Aguirre, C. A., Gullapalli, S., De La Torre, M. F., Lam, A., Weese, J. L., & Hsu, W. H. (2017). Learning to Filter Documents for Information Extraction using Rapid Annotation. Proceedings of the 1st International Conference on Machine Learning and Data Science (MLDS 2017), Noida, India, December 14-15, 2017.
  14. Yates, H., Chamberlain, B., & Hsu, W. (2017). A Spatially Explicit Classification Model for Affective Computing in Built Environments. Proceedings of the 7th AAAC International Conference on Affective Computing and Intelligent Interaction (ACII 2017) Workshops and Demos, San Antonio, TX, USA, October 23-26, 2017.
  15. Yates, H., Hsu, W., Chamberlain, B., & Norman, G. (2017). Arousal Detection for Biometric Data in Built Environments using Machine Learning. Working Notes of the 1st International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Artificial Intelligence in Affective Computing, Melbourne, Australia, August 20, 2017.
  16. Weese, J. L. & Hsu, W. H. (2016). Work in Progress: Data Explorer – Assessment Data Integration, Analytics, and Visualization for STEM Education Research. Proceedings of the 123rd Annual American Society for Engineering Education Annual Conference and Exposition (ASEE 2016), New Orleans, LA, USA, June 26-29, 2016.
  17. Yang, M. & Hsu, W. H. (2016). HDPauthor: A New Hybrid Author-Topic Model using Latent Dirichlet Allocation and Hierarchical Dirichlet Processes. Proceedings of the 25th International World Wide Web Conference (WWW 2016) Workshop on Natural Language Processing for Informal Text (NLPIT 2016), pp. 619-624. Montréal, QC, Canada, April 12, 2016.
  18. Yang, M. & Hsu, W. H. (2015). Incorporation of Latent Dirichlet Allocation for Aspect-Level Sentiment into Hierarchical Dirichlet Process-Based Topic Models. Proceedings of the 7th Language and Technology Conference (LTC 2015): Human Language Technologies as a Challenge for Computer Science and Linguistics, in press. Poznań, Poland, November 27-29, 2015.
  19. Murphy, J. C., Hsu, W. H., Elshamy, W., Kallumadi, S. T., & Volkova, S. (2014). Greensickness and HPV: A Comparative Analysis? In Gniady, T., McAbee, K., & Murphy, J. C., eds., New Technologies in Renaissance Studies II volume 4, pp. 171-197. Toronto and Tempe, AZ, USA: Iter and Arizona Center for Medieval and Renaissance Studies.
  20. Hsu, W. H., Koduru, P., & Zhai, C. (2013). Heterogeneous Information Networks for Text-Based Link Mining: A Position Paper on Visualization and Structure Learning Methods. Working Notes of the 2nd International Workshop on Heterogeneous Information Network Analysis (HINA 2013). Beijing, China.
  21. Hsu, W. H. & Koduru, P. (2012). Opinion Mapping: Information Visualization Approaches for Comparative Sentiment Analysis. Proceedings of the 2nd European Workshop on Human-Computer Interaction and Information Retrieval (EuroHCIR 2012), pp. 25-28. Nijmegen, The Netherlands, August 24-25, 2012.
  22. Hsu, W. H., Abduljabbar, M., Osuga, R., Lu, M., & Elshamy, W. (2012). Visualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data Mining Research Directions. Proceedings of the 2nd European Workshop on Human-Computer Interaction and Information Retrieval (EuroHCIR 2012), pp. 43-46. Nijmegen, The Netherlands, August 24-25, 2012.
  23. Volkova, S., Caragea, D., Hsu, W. H., Drouhard, J., & Fowles, L. (2010). Boosting Biomedical Entity Extraction by using Syntactic Patterns for Semantic Relation Discovery. Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2010), Toronto, ON, Canada, August 31 - September 3, 2010.
  24. Weninger, T., Ramachandran, S., Greene, D., Hart, J., Kancherlapalli, A., Hsu, W. H. & Han, J. (2010). Speech-Assisted Radiology System for Retrieval, Reporting and Annotation. Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA, July 25-28, 2010.
  25. Elshamy, W., Caragea, D., & Hsu, W. (2010). KSU KDD: Word sense induction by clustering in topic space. Proceedings of the Association for Computational Linguistics 5th International Workshop on Semantic Evaluation, pp. 367–370. Uppsala, Sweden, July, 2010.
  26. Roy Chowdhury, S., Scoglio, C., & Hsu, W. H. (2010). Simulative modeling to control the foot and mouth disease epidemic. Proceedings of the International Conference on Computational Science (ICCS 2010) Workshop 27: Frontiers in the Computational Modeling of Disease Spreading. Procedia Computer Science, 2010(1), pp. 2261 - 2270. Amsterdam, The Netherlands, May 31 - June 2, 2010.
  27. Volkova, S., & Hsu, W. H. (2010). Computational knowledge and information management in veterinary epidemiology. Proceedings of the 8th IEEE International Conference on Intelligence and Security Informatics (ISI 2010). Vancouver, BC, Canada, May 23-26, 2010.
  28. Volkova, S., Caragea, D., Hsu, W., & Bujuru, S. (2010). Animal disease event recognition and classification. Proceedings of the First International Workshop on Web Science and Information Exchange in the Medical Web (MedEx 2010). Raleigh, NC, USA, April 30, 2010.
  29. Weninger, T., Han, J., & Hsu, W. H. (2010). CETR - content extraction via tag ratios. In Proceedings of the 19th International World Wide Web Conference (WWW 2010). Raleigh, NC, USA, April 26-30, 2010.
  30. Xia, J., Caragea, D. and Hsu, W. (2009). Bi-relational network analysis using a fast random walk with restart. Proceedings of the IEEE International Conference on Data Mining (ICDM 2009). Miami, FL, USA, December 6-9, 2009.
  31. Weninger, T., Greene, D., Hart, J., Hsu, W. H., & Ramachandran, S. (2009). Speech-assisted radiology system for retrieval, reporting and annotation, Proceedings of the 22nd IEEE Conference on Computer Based Medical Systems (CBMS-2009), Albuquerque, NM, USA, August 2-4, 2009.
  32. Weninger, T., Howell, R. R., & Hsu, W. H. (2009). Graph drawing heuristics for path finding in large dimensionless graphs. Proceedings of the 2009 International Conference on Artificial Intelligence (ICAI 2009). Las Vegas, NV, USA, July 13-16, 2009.
  33. Xia, J., & Hsu, W. H. (2009). Protein protein interaction analysis using fast random walk. Proceedings of the 2009 International Conference on Artificial Intelligence (IC-AI 2009), pp. 857-863. Las Vegas, NV, USA, July 13-16, 2009.
  34. Caragea, D., Bahirwani, V., Aljandal, W., & Hsu, W. H. (2009). Ontology-based link prediction in the LiveJournal social network. Proceedings of the 8th Symposium on Abstraction, Reformulation and Approximation (SARA 2009). Lake Arrowhead, CA, USA, July 7-10, 2009.
  35. Aljandal, W., Hsu, W. H., Bahirwani, V., & Caragea, D. (2009) Ontology-Aware Classification and Association Rule Mining for Interest and Link prediction in Social Networks. Proceedings of the Association for the Advancement of Artificial Intelligence Spring Symposium on Social Semantic Web (AAAI SSW 2009), Stanford, CA, USA, March 23-25, 2009.
  36. Aljandal, W., Hsu, W. H., & Xia, J. (2009). Predicting Protein-Protein Interactions using Numerical Associational Features. Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2009). Nashville, TN, USA, March 30 - April 2, 2009.
  37. Hsu, W. H., Weninger, T., & Paradesi, M. S. R. (2008). Predicting Links and Link Change in Friends Networks - Supervised Time Series Learning with Imbalanced Data, Proceedings of the 18th International Conference on Artificial Neural Networks in Engineering (ANNIE 2008). St. Louis, MO, USA, November 9-12, 2008.
  38. Weninger, T. & Hsu, W. H. (2008). Web Content Extraction Through Histogram Clustering. Proceedings of the 18th International Conference on Artificial Neural Networks in Engineering (ANNIE 2008). St. Louis, MO, USA, November 9-12, 2008.
  39. Aljandal, W., Hsu, W. H., Bahirwani, V., Caragea, D., & Weninger, T. (2008). Validation-Based Normalization and Selection of Interestingness Measures for Association Rules. Proceedings of the 18th International Conference on Artificial Neural Networks in Engineering (ANNIE 2008). St. Louis, MO, USA, November 9-12, 2008.
  40. Weninger, T. & Hsu, W. H. Text Extraction from the Web via Text-To-Tag Ratio, Proceedings of the 19th International Conference on Database and Expert Systems Applications (DEXA 2008) Workshop on Text-based Information Retrieval. Turin, Italy, Sept 1-5, 2008.
  41. Bahirwani, V., Caragea, D., Aljandal, W. & Hsu, W. H. (2008). Ontology Engineering and Feature Construction for Predicting Friendship Links in the Live Journal Social Network. Proceedings of the Second Workshop on Social Network Mining and Analysis, held in conjunction with the Association for Computing Machinery International Conference on Knowledge Discovery and Data Mining (SNA-KDD 2008). Las Vegas, NV, USA, August 24-27, 2008.
  42. Paradesi, M. S. R., Caragea, D., & Hsu, W. H. (2007). Structural Prediction of Protein-Protein Interactions in Saccharomyces cerevisiae. Proceedings of IEEE 7th International Symposium on BioInformatics and BioEngineering (BIBE 2007), pp. 1270-1274. Boston, MA, October, 2007.
  43. Hsu, W. H., Lancaster, J. P., Paradesi, M. S. R., & Weninger, T. (2007). Structural Link Analysis from User Profiles and Friends Networks: A Feature Construction Approach, Proceedings of the 1st International Conference on Weblogs and Social Media (ICWSM 2007), pp. 75-80. Boulder, CO, USA, March, 2007.
  44. Paradesi, M. S. R., Wang, L., Brown, S. J., & Hsu, W. H. (2006). Mining Domain Association Rules From Protein-Protein Interaction data, Intelligent Engineering Systems through Artificial Neural Networks, vol. 16, pp. 213-218. St. Louis, MO, USA, November 2006.
  45. Hsu, W. H., King, A. L., Paradesi, M., Pydimarri, T., & Weninger, T. (2006). Collaborative and Structural Recommendation of Friends using Weblog-based Social Network Analysis. Computational Approaches to Analyzing Weblogs - Papers from the 2006 Spring Symposium, Nicolov, N., Salvetti, F., Liberman, M., & Martin, J. H., eds. pp. 24-31. AAAI Press Technical Report SS-06-03. Stanford, CA, USA, March 27-29, 2006.
  46. Koduru, P., Hsu, W. H., Das, S., Welch, S. M., & Roe, J. L. (2005). Dynamic Systems Prediction using Temporal Artificial Neural Networks and Multi-objective Genetic Algorithm. Proceedings of the International Association of Science and Technology for Development (IASTED) Conference on Computational Intelligence, pp. 214-219. Calgary, AB, Canada, July 4-6, 2005.
  47. Hsu, W. H. (2005). Relational Graphical Models for Collaborative Filtering and Recommendation of Computational Workflow Components. Working Notes of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-2005), Workshop 20: Multi-Agent Information Retrieval and Recommender Systems, pp. 18-22. Edinburgh, UK, July 31, 2005.
  48. Guo, H. & Hsu, W. H. (2004). A Learning-Based Algorithm Selection Meta-Reasoner for the Real-Time MPE Problem. Proceedings of the 17th Australian Joint Conference on Artificial Intelligence (AI 2004), pp. 307-318. Cairns, QLD, Australia, December 4-6, 2004.
  49. Guo, H., Bodhireddy, P., & Hsu, W. H. (2004). An ACO Algorithm for the Most Probable Explanation Problem. Proceedings of the 17th Australian Joint Conference on Artificial Intelligence (AI 2004), pp. 778-790. Cairns, QLD, Australia, December 4-6, 2004.
  50. Harmon, S. J. , Rodríguez, E. , Zhong, C. A. & Hsu, W. H. (2004). Empirical Comparison of Incremental Learning Strategies for Genetic Programming-Based Keep-Away Soccer Agents. Proceedings of the AAAI 2004 Fall Symposium on Artificial Multi-Agent Learning. Washington, DC, USA, October 22-24, 2004.
  51. Hsu, W. H. & Joehanes, R. (2004). Permutation Genetic Algorithms for Score-Based Bayesian Network Structure Learning. Proceedings of the International Conference on Computing, Communications and Control Technologies (CCCT 2004), pp. 273-280, Austin, TX, August 14-17, 2004.
  52. Hsu, W. H. & Gustafson, S. M. (2002). Genetic Programming and Multi-Agent Layered Learning by Reinforcements. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 764 - 771. New York, NY, USA, July 9-13, 2002.
  53. Hsu, W. H., Guo, H., Perry, B. B. & Stilson, J. A. (2002). A Permutation Genetic Algorithm for Variable Ordering in Learning Bayesian Networks from Data. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 383 - 390. New York, NY, USA, July 9-13, 2002.
  54. Gustafson, S. M. & Hsu, W. H. (2001). Layered Learning in Genetic Programming for a Cooperative Robot Soccer Problem. Proceedings of the 4th European Conference on Genetic Programming (EuroGP 2001), Springer LNCS 2038, pp. 291 - 301. Lake Como, Italy, April 18-20, 2001.
  55. Hsu, W. H., Auvil, L. S., Pottenger, W. M., Tcheng, D., & Welge, M. (1999). Self-Organizing Systems for Knowledge Discovery in Databases. Proceedings of the International Joint Conference on Neural Networks (IJCNN 1999). Washington, DC, USA, July 10-16, 1999.
  56. Hsu, W. H. & Ray, S. R. (1999). Construction of Recurrent Mixture Models for Time Series Classification. Proceedings of the International Joint Conference on Neural Networks (IJCNN 1999). Washington, DC, USA, July 10-16, 1999.
  57. Hsu, W. H. Welge, M., Wu, J., & Yang, T. (1999). Genetic Algorithms for Selection and Partitioning of Attributes in Large-Scale Data Mining Problems. Freitas, A. A. (ed.), Data Mining with Evolutionary Algorithms: Research Directions - Papers from the Joint AAAI-GECCO Workshop, pp. 1 - 7, AAAI Press Technical Report WS-99-06. Orlando, FL, USA, July 18, 1999.
  58. Grois, E., Hsu, W. H., Voloshin, M., & Wilkins, D. C. (1998). Bayesian Network Models for Automatic Generation of Crisis Management Training Scenarios. Proceedings of the 10th Innovative Applications of Artificial Intelligence Conference (IAAI 1998), pp. 1113-1120. Madison, WI, USA, July 26-30, 1998.
  59. Hsu, W. H., Gettings, N. D., Lease, V. E., Pan, Y., & Wilkins, D. C. (1998). Heterogeneous Time Series Learning for Crisis Monitoring. Danyluk, A., Fawcett, T., & Provost, F. (eds.), Predicting the Future: AI Approaches to Time Series Problems - Papers from the Joint AAAI-ICML Workshop, pp. 34-41. AAAI Press Technical Report WS-98-07. Madison, WI, USA, July 26-30, 1998.
  60. Hsu, W. H. & Ray, S. R. (1998). A New Mixture Model for Concept Learning From Time Series (Extended Abstract). Danyluk, A., Fawcett, T., & Provost, F. (eds.), Predicting the Future: AI Approaches to Time Series Problems - Papers from the Joint AAAI-ICML Workshop, pp. 42-43, AAAI Press Technical Report WS-98-07. Madison, WI, USA, July 27, 1998.
  61. Hsu, W. H. & Ray, S. R. (1998). Quantitative Model Selection for Heterogeneous Time Series. In Engels, R., Verdenius, F., & Aha, D. (eds.), The Methodology of Applying Machine Learning - Papers from the Joint AAAI-ICML Workshop, pp. 8-12. AAAI Press Technical Report WS-98-26. Madison, WI, USA, July 27, 1998.
  62. Hsu, W. H., Gettings, N. D., Lease, V. E., Pan, Y., & Wilkins, D. C. (1998). Crisis Monitoring: Methods for Heterogeneous Time Series Learning. Proceedings of the International Workshop on Multistrategy Learning (MSL 1998). Desenzano Del Garda, Italy, June 11-13, 1998.
  63. Hsu, W. H. (1997). A Position Paper on Statistical Inference Techniques which Integrate Bayesian and Stochastic Neural Network Models. Proceedings of the International Conference on Neural Networks (ICNN 1997), pp. 1972-1977. Houston, TX, USA, June 9-12, 1997.
  64. Delcher, A., Kasif, S., Goldberg, H., & Hsu, W. (1993). Probabilistic Prediction of Protein Secondary Structure Using Causal Networks. Proceedings of the 11th National Conference on Artificial Intelligence (AAAI 1993), pp. 316-321. Washington, DC, USA, July 11-15, 1993.
  65. Delcher, A., Kasif, S., Goldberg, H., & Hsu, W. (1993). Protein Secondary Structure Modelling with Probabilistic Networks. Proceedings of the First International Conference on Intelligent Systems for Molecular Biology (ISMB 1993), pp. 109 - 117. Bethesda, MD, USA, July 6-9, 1993.