Home             |                 Publications           |                Miscellaneous

 

 

 

 

 

 

Journal Papers:

2015

Hongyu Guo, Accelerated Continuous Conditional Random Fields For Load Forecasting, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2015. [PDF]

2012

Hongyu Guo and Sylvain Letourneau, Iterative Classification for Multiple Target Attributes, Journal of Intelligent Information Systems(JIIS), Springer Netherlands, 2012. [PDF]

Hongyu Guo, Herna L. Viktor, and Eric Paquet, Reducing the Size of Databases for Multirelational Classification: a Subgraph-based Approach, Journal of Intelligent Information Systems(JIIS), Springer Netherlands, 2012.[PDF]

2011

Hongyu Guo, Herna L. Viktor, and Eric Paquet, Privacy Disclosure and Preservation in Learning with Multi-relational Databases, Journal of Computing Science and Engineering (JCSE), Special Issue on "Privacy Aspects of Data Mining", 2011. [PDF]

2008

Hongyu Guo and Herna L. Viktor, Learning from Skewed Class Multi-relational Databases, Journal of Fundamenta Informaticae (FI), Special Issue on "Multi-relational Data Mining", Volume 89, Issue 1, pages 69-94, 2008

Hongyu Guo and Herna L. Viktor, Multirelational Classification: A Multiple View Approach, Knowledge and Information Systems (KAIS),  Volume 17, Issue 3, pages 287-312, 2008.[PDF]

2004

Hongyu Guo and Herna L. Viktor, Learning from Imbalanced Data Sets with Boosting and Data Generation: The DataBoost-IM Approach, ACM SIGKDD Explorations, 6(1),2004,30-39. [PDF]

 

Conference Papers/Workshop Papers/Chapters in Books:

2018

Martin Renqiang Min, Hongyu Guo, and Dinghan Shen, Parametric t-Distributed Stochastic Exemplar-centered Embedding, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2018) [PDF]

 

2017

Martin Renqiang Min, Hongyu Guo, and Dongjin Song, Exemplar-Centered Supervised Shallow Parametric Data Embedding, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2017). [PDF]

 

Hongyu Guo, Colin Cherry, and Jiang Su, End-to-End Multi-View Networks for Text Classification. [arXiv]

 

Hongyu Guo, A Deep Network with Visual Text Composition Behavior, Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017) [PDF]

 

 

2016

Hongyu Guo, Accelerated Continuous Conditional Random Fields For Load Forecasting (extended abstract), 32nd IEEE International Conference on Data Engineering (ICDE2016) [PDF]

 

Xiaodan Zhu, Parinaz Sobhani, and Hongyu Guo: DAG-structured Recurent Neural Networks for Semantic Compositionality, Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2016) [PDF]

 

2015

Hongyu Guo, Generating Text with Deep Reinforcement Learning, Deep Reinforcement Learning Workshop @NIPS 2015 [Poster][PDF]

 

Colin Cherry, Hongyu Guo, and Chengbi Dai, NRC: Infused Phrase Vectors for Named Entity Recognition in Twitter, Proceedings of Noisy User-generated Text (W-NUT) Workshop @ACL2015, July 2015. [PDF]

 

Colin Cherry and Hongyu Guo: The Unreasonable Effectiveness of Word Representations for Twitter Named Entity Recognition. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2015). [PDF]

 

Boxing Chen and Hongyu Guo: Representation Based Translation Evaluation Metrics.  Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL 2015). [PDF]

 

Boxing Chen, Hongyu Guo and Roland Kuhn. 2015. Multi-level Evaluation for Machine Translation. In: Proceedings of WMT @EMNLP2015. Lisbon, Portugal. September.

 

Xiaodan Zhu, Hongyu Guo, and Parinaz Sobhani: Neural Networks for Integrating Compositional and Non-compositional Sentiment in Sentiment Composition, Proceedings of Joint conference on Lexical and Computational Semantics. Denver, Colorado (*SEM 2015). [PDF]

[this paper won the Best Paper Award]

 

Xiaodan Zhu, Parinaz Sobhani, and Hongyu Guo: Long Short-Term Memory over Recursive Structures, Proceedings of International Conference on Machine Learning (ICML 2015). [PDF]

 

Eric Paquet, Herna Viktor, and Hongyu Guo, Data Mining in Finance: Current Advances and Future Challenges, book chapter in Big Data Analysis: New Algorithm for a New Society, Springer, Editors: Nathalie Japkowicz and Jerzy Stefa, 2015.

 

Chunsheng Yang, Qingfeng Lou, Jie Liu, Hongyu Guo, and Yun Bai:Particle Filter-Based Approach to Estimate Remaining Useful Life for Predictive Maintenance. IEA/AIE 2015

2014

Hongyu Guo, Xiaodan Zhu, and Martin Renqiang Min, A Deep Learning Model for Structured Outputs with High-order Interaction. Representation and Learning Methods for Complex Outputs Workshop @NIPS2014. [PDF]

Xiaodan Zhu, Hongyu Guo, Saif Mohammad, and Svetlana Kiritchenko: An Empirical Study on the Effect of Negation Words on Sentiment.  In Proceedings of the 52th Annual Meeting of the Association for Computational Linguistics (ACL 2014). Baltimore, USA. 2014: 304-313 .[PDF]

Hongyu Guo, Sylvain Létourneau, and Chunsheng Yang: A Data Driven Approach for Smart Lighting. IEA/AIE (2) 2014: 308-317

Chunsheng Yang, Sylvain Létourneau, and Hongyu Guo: Developing Data-driven Models to Predict BEMS Energy Consumption for Demand Response Systems. IEA/AIE (1) 2014: 188-197

2013

Hongyu Guo, Modeling Short-Term Energy Load with Continuous Conditional Random Fields, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2013), Prague, Czech Republic .[PDF]

2012

Michelangelo Ceci, Annalisa Appice, Herna L. Viktor, Donato Malerba, Eric. Paquet, and Hongyu Guo, Transductive Relational Classification in the Co-Training Paradigm, Proceedings of the 8th International Conference on Machine Learning and Data Mining (MLDM 2012), July 13-20, 2012, Berlin, Germany. [this paper won the Best Paper Award]

Eric Paquet, Hern L. Viktor, and Hongyu Guo, Learning with Aggregation and Correlation in the Presence of Large Fluctuations, Proceedings of the New Frontiers in Mining Complex Patterns  Workshop (NFMCP2012), in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’ 12), 24-28 September 2012, Bristol, UK

2011

Hongyu Guo, Herna L. Viktor, and Eric Paquet, Privacy Leakage in Multi-relational Learning via Unwanted Classification Models,  in Proc. 21st IBM Centre for Advanced Studies Conference (CASCON 2011), Toronto, Canada, Nov. 2011. [PDF]

Eric Paquet, Hern L. Viktor, and Hongyu Guo, To Aggregate or Not to Aggregate: That is the Question, in Proc. International Conference on Knowledge Discovery and Information Retrieval (KDIR 2011), Paris, France, Oct. 2011.

Pengcheng Xi, Hongyu Guo, and Chang Shu, Human Body Shape Prediction and Analysis Using Predictive Clustering Tree, in Proc. 3D Imaging.Modeling.Processing.Visualization.Transmission (3DIMPVT 2011), Hangzhou, China, May 2011. [PDF]

2010

Hongyu Guo, Herna L. Viktor, and Eric Paquet, Identifying and Preventing Data Leakage in Multi-relational Classification, in Proc. IEEE International Workshop on Privacy Aspects of Data Mining (PADM 2010), in conjunction with IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia, December 2010. [PDF]

2007

Hongyu Guo, Herna L. Viktor, and Eric Paquet, Pruning Relations for Substructure Discovery of Multi-relational Databases, in Proc. 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2007), Warsaw, Poland, September 2007. [PDF]

Hongyu Guo and Herna L. Viktor, Mining Imbalanced Classes in Multirelational Classification, Proceedings of the 6th Multi-Relational Data Mining Workshop(PKDD-MRDM'07), in conjunction with 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'07), Warsaw, Poland, September 2007. [PDF]

Eric Paquet, Herna L. Viktor, Hongyu Guo, and Isis Pena Sanchez, Constrained Virtual Tailoring from Anthropometric Data, 3-D Shape and Data Mining, Proceedings of the Second International WEAR Conference (WEAR'02), Alberta, Canada, Aug, 2007.

2006

Hongyu Guo and Herna L. Viktor, Mining Relational Data through Correlation-based Multiple View Validation, in Proc. the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD 2006), Philadelphia, PA, August 2006. [PDF]

Herna L. Viktor, Eric Paquet and Hongyu Guo, Measuring to Fit: Virtual Tailoring through Cluster Analysis and Classification, in Proc. 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2006), Berlin, Germany, September 2006. [PDF]. [this paper won the Distinguished Papers Award]

Hongyu Guo and Herna L. Viktor, Multi-view Artificial Neural Networks for Multi-relational Classification, in Proc. IEEE International Joint Conference on Neural Networks (IJCNN 2006), Vancouver, BC, July. 2006. IEEE Press. 

2005

Hongyu Guo and Herna L. Viktor, Mining Relational Databases with Multi-view Learning, in Proc. the 4th Multi-Relational Data Mining Workshop (KDD/MRDM'05), in conjunction with the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2005), Chicago, IL, Aug. 2005. ACM Press. [PDF]

2004

Herna L. Viktor and Hongyu Guo, Multiple Classifier Prediction Improvements against Imbalanced Datasets through Adding Synthetic Examples, in Proc. the 10th International Workshop on Statistical Pattern Recognition, (S+SSPR 2004), Lisbon, Portugal, Aug. 2004.

Hongyu Guo and Herna L. Viktor, Boosting with Data Generation: Improving Classification of Hard to Learn Examples, in Proc. the 17th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems (IEA/AIE 2004), Ottawa, ON, May 2004.
 

 

 

Theses:

Hongyu Guo, Learning from Multirelational Data through Multiple Views, PhD Thesis, University of Ottawa, 2008.[PDF]

Hongyu Guo, Multiple Classifiers combination through Ensemble and Data Generation, Master's Thesis, University of Ottawa, 2004. [PDF]