About Me

 

 

Research

My primary area of research is machine learning, with an emphasis on learning useful data representations, and learning accurate classification models under various circumstances. Natural language processing, computer vision and bioinformatics are my application areas. My research covers the following topics:

  • Generalized information adaptation: domain adaptation, cross-lingual learning, zero-shot learning
  • Learning with complex outputs: multi-label learning, sequence labeling
  • Heterogeneous learning: multi-label, multi-view, multi-instance learning
  • Representation learning: dimensionality reduction and feature selection, deep learning
  • Active learning
  • Learning graphical models
  • Optimization

Current Group Members

  • Feipeng Zhao
  • Chen Shen
  • Meng Ye

Alumni

  • Min Xiao (PhD, 2011-- 2015; now a Lead Data Scientist at ADP)
  • Xin Li (PhD, 2011-- 2015; now a Senior Data Scientist at Adelphic)
  • Suicheng Gu (PDF 2010; now at Google)
  • Xiangwei Meng (M.Sc. 2015)
  • Richard Hart (M.Sc. 2011)
  • Mike Bissell (B.Sc. 2012)
  • Bob Suhendra (B.Sc. 2010)
  • John P. Ihlenfeldt (2015)

Papers

  • F. Zhao and Yuhong Guo (2016),   ``Improving Top-N Recommendation with Heterogeneous Loss". In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-16).  [pdf]

  • F. Zhao, M. Xiao and Yuhong Guo (2016),   ``Predictive Collaborative Filtering with Side Information". In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-16).  [pdf]

  • X. Li, Yuhong Guo and D. Schuurmans (2015),  ``Semi-Supervised Zero-Shot Classification with Label Representation Learning". In Proceedings of the IEEE International Conference on Computer Vision (ICCV-15).  [pdf]

  • M. Xiao and Yuhong Guo (2015),  ``Annotation Projection-based Representation Learning for Cross-lingual Dependency Parsing". `` In Proceedings of the Conference on Computational Natural Language Learning (CoNLL-15)  [pdf]

  • M. Xiao and Yuhong Guo (2015),  ``Learning Hidden Markov Models with Distributed State Representations for Domain Adaptation". In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-15).  [pdf]

  • M. Xiao and Yuhong Guo (2015),  ``Semi-Supervised Subspace Co-Projection for Multi-Class Heterogeneous Domain Adaptation". In Proceedings of the European Conference on Machine Learning (ECML-15).  [pdf]

  • F. Zhao and Yuhong Guo (2015),   ``Semi-supervised Multi-label Learning with Incomplete Labels". In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-15).  [pdf]

  • X. Li and Yuhong Guo (2015),   ``Multi-label Classification with Feature-aware Non-linear Label Space Transformation". In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-15).  [pdf]

  • X. Li and Yuhong Guo (2015),  ``Max-Margin Zero-Shot Learning for Multi-class Classification". In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS-15).  [pdf]

  • X. Li, F. Zhao and Yuhong Guo (2015),  ``Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels". In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS-15).  [pdf]

  • X. Li and Yuhong Guo (2014),  ``Multi-level Adaptive Active Learning for Scene Classication". In Proceedings of the European Conference on Computer Vision (ECCV-14).  [pdf]

  • M. Xiao and Yuhong Guo (2014),   ``Feature Space Independent Semi-Supervised Domain Adaptation via Kernel Matching". IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI-14), Volume 37, Issue 1, Pages 54-66.  [pdf]

  • X. Li and Yuhong Guo (2014),  ``Bi-Directional Representation Learning for Multi-label Classification". In Proceedings of the European Conference on Machine Learning (ECML-14).  [pdf]

  • X. Li, F. Zhao and Yuhong Guo (2014),   ``Multi-label Image Classification with A Probabilistic Label Enhancement Model". In Proceedings of the thirtieth Conference on Uncertainty in Artificial Intelligence (UAI-14).  [pdf]

  • M. Xiao and Yuhong Guo (2014),   ``Distributed Word Representation Learning for Cross-lingual Dependency Parsing". In Proceedings of the Conference on Computational Natural Language Learning (CoNLL-14).  [pdf]

  • X. Li and Yuhong Guo (2014),   ``Latent Semantic Representation Learning for Scene Classification". In Proceedings of the International Conference on Machine Learning (ICML-14).  [pdf]

  • M. Xiao and Yuhong Guo (2014),  ``Semi-supervised Matrix Completion for Cross-Lingual Text Classification". In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14).  [pdf]

  • F. Mirzazadeh, Yuhong Guo, and D. Schuurmans (2014),  ``Convex Co-embedding". In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14).  [pdf]

  • M. Xiao and Yuhong Guo (2013),   ``A Novel Two-Step Method for Cross Language Representation Learning". In Advances in Neural Information Processing Systems (NIPS-13).  [pdf]

  • Yuhong Guo (2013),   ``Robust Transfer Principal Component Analysis with Rank Constraints". In Advances in Neural Information Processing Systems (NIPS-13).  [pdf]

  • M. Xiao, F. Zhao and Yuhong Guo (2013),   ``Learning Latent Word Representations for Domain Adaptation using Supervised Word Clustering". In Proceedings of the Conference on Empirical Methods on Natural Language Processing (EMNLP-13).  [pdf]

  • M. Xiao and Yuhong Guo (2013),   ``Semi-Supervised Representation Learning for Cross-Lingual Text Classification". In Proceedings of the Conference on Empirical Methods on Natural Language Processing (EMNLP-13).  [pdf]

  • Yuhong Guo and D. Schuurmans (2013),  ``Multi-label Classification with Output Kernels". In Proceedings of the European Conference on Machine Learning (ECML-13).  [pdf]

  • M. Xiao and Yuhong Guo (2013),   ``Online Active Learning for Cost-Sensitive Domain Adaptation". In Proceedings of the Conference on Computational Natural Language Learning (CoNLL-13).  [pdf]

  • X. Li and Yuhong Guo (2013),   ``Active Learning with Multi-label SVM Classification". In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-13).  [pdf]  *[code]*

  • Yuhong Guo and W. Xue (2013),   ``Probabilistic Multi-label Classification with Sparse Feature Learning". In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-13).  [pdf]

  • Yuhong Guo (2013),  ``Convex Subspace Representation Learning from Multi-view Data". In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13).  [pdf]

  • X. Li and Yuhong Guo (2013),   ``Adaptive Active Learning for Image Classification". In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR-13).  [pdf]  *[code]*

  • M. Xiao and Yuhong Guo (2013),   ``Domain Adaptation for Sequence Labeling Tasks with a Probabilistic Language Adaptation Model". In Proceedings of the International Conference on Machine Learning (ICML-13).  [pdf]

  • F. Huang, A. Ahuja, D. Downey, Y. Yang, Yuhong Guo and A. Yates (2013),  `` Learning Representations for Weakly Supervised Natural Language Processing Tasks". In Computational linguistics, 2013.  [pdf]

  • L. Lan, N. Djuric, Yuhong Guo and S. Vucetic (2013),  `` MS-kNN: Protein Function Prediction by Integrating Multiple Data Sources". BMC Bioinformatics, Vol. 14(suppl. 3):S8, 2013.  [pdf]

  • P. Radivojac, W.T. Clark, ..., L. Lan, N. Djuric, Yuhong Guo, S. Vucetic, et al. (2013),  `` A Large-scale Evaluation of Computational Protein Function Prediction". Nature Method, Vol. 10(3), pp. 221-229, 2013.  [pdf]

  • Yuhong Guo and M. Xiao (2012),  ``Cross Language Text Classification via Multi-view Subspace Learning". In NIPS workshop on xLiTe: Cross-Lingual Technologies.  

  • M. Xiao and Yuhong Guo (2012),   ``Multi-View AdaBoost for Multilingual Subjectivity Analysis". In Proceedings of the International Conference on Computational Linguistics (COLING-12).  [pdf]

  • M. Xiao, Yuhong Guo and A. Yates (2012),   ``Semi-supervised Representation Learning for Domain Adaptation using Dynamic Dependency Networks". In Proceedings of the International Conference on Computational Linguistics (COLING-12).  [pdf]

  • Q. Liu, Yuhong Guo, J. Wu, and G. Wang (2012),  ``Dynamic Grouping Strategy in Cloud Computing". In Proceedings of the 2nd International Conference on Cloud and Green Computing (CGC-12). (Best Student Paper Award)  [pdf]

  • S. Gu and Yuhong Guo (2012),  ``Max-Margin Ratio Machine". In proceedings of JMLR workshop and conference, Asian Conference on Machine Learning (ACML-12).  [pdf]

  • X. Li and Yuhong Guo (2012),  ``An Object Co-occurrence Assisted Hierarchical Model for Scene Understanding". In Proceedings of the British Machine Vision Conference (BMVC-12).  [pdf]

  • Yuhong Guo and D. Schuurmans (2012),  ``Semi-Supervised Multi-label Classification: A Simultaneous Large-margin, Subspace Learning Approach". In Proceedings of the European Conference on Machine Learning (ECML-12).  [pdf]

  • M. Xiao and Yuhong Guo (2012),  ``Semi-Supervised Kernel Matching for Domain Adaptation". In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12).  [pdf]

  • S. Gu and Yuhong Guo (2012),  ``Learning SVM Classifiers with Indefinite Kernels". In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12). (Outstanding Paper Award)  [pdf]

  • Yuhong Guo and M. Xiao (2012),  ``Transductive Representation Learning for Cross-Lingual Text Classification". In Proceedings of the IEEE International Conference on Data Mining (ICDM-12).  [pdf]

  • Yuhong Guo and M. Xiao (2012),  ``Cross Language Text Classification via Subspace Co-regularized Multi-view Learning". In Proceedings of the Twenty-Nineth International Conference on Machine Learning (ICML-12).  [pdf]

  • V. Ouzienko, Yuhong Guo, and Z. Obradovic (2011),  ``A Decoupled Exponential Random Graph Model for Prediction of Structure and Attributes in Temporal Social Networks". Statistical Analysis and Data Mining Journal.  

  • L. Lan, N. Djuric, Yuhong Guo and S. Vucetic (2011),  ``Protein Function Prediction by Integrating Different Data Sources". AFP/CAFA 2011.  [pdf]

  • Y. Wang, Yuhong Guo and J. Wu (2011),  ``Making Many People Happy: Greedy Solutions for Content Distribution". In Proceedings of the International Conference on Parallel Processing (ICPP-11).  [pdf]

  • Yuhong Guo and D. Schuurmans (2011),  ``Adaptive Large Margin Training for Multilabel Classification". In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI-11).  [pdf]

  • Yuhong Guo and S. Gu (2011),  ``Multi-label Classification using Conditional Dependency Networks''. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-11).  [pdf]

  • Yuhong Guo (2010),  ``Active Instance Sampling via Matrix Partition''. In Proceedings of Advances in Neural Information Processing Systems (NIPS-10).  [pdf]

  • Y. Shi, Yuhong Guo, G. Lin, and D. Schuurmans (2010),  ``Kernel-based Gene Regulatory Network Inference''. In Proceedings of the LSS Computational Systems Bioinformatics Conference (CSB-10).  [pdf]

  • K. Rsitovski, D. Das, V. Ouzienko, Yuhong Guo, and Z. Obradovic (2010),  ``Regression Learning with Multiple Noisy Oracles''. In Proceedings of European Conference on Artificail Intelligence (ECAI-10).  [pdf]

  • V. Ouzienko, Yuhong Guo, and Z. Obradovic (2010),  ``Prediction of Attributes and Links in Temporal Social Networks''. In Proceedings of European Conference on Artificail Intelligence (ECAI-10).  [pdf]

  • Yuhong Guo (2009),  ``Supervised Exponential Family PCA via Global Optimization''. [pdf]

  • Yuhong Guo (2009),  ``Max-Margin Multiple-Instance Learning via Semidefinite Programming''. In Advances in Machine Learning, Asian Conference on Machine Learning (ACML-09).  [pdf]

  • Yuhong Guo and Dale Schuurmans (2009),  ``A Reformulation of Support Vector Machines for General Confidence Functions". In Advances in Machine Learning, Asian Conference on Machine Learning (ACML-09).  [pdf] 

  • Yuhong Guo (2008),  ``Supervised Exponential Family Principal Component Analysis via Convex Optimization''. In Proceedings of Advances in Neural Information Processing Systems (NIPS-08). [pdf]

  • Yuhong Guo and Dale Schuurmans (2008),  ``Efficient Global Optimization for Exponential Family PCA and Low-rank Matrix Factorization". In Allerton Conference on Communication, Control, and Computing (Allerton-08). [pdf] 

  • Yuhong Guo (2007),  ``Learning Bayesian Networks from Data: Structure Optimization and Parameter Estimation".  Ph.D. Thesis, Department of Computing Science, University of Alberta.

  • Yuhong Guo and Dale Schuurmans (2007),  ``Convex Relaxations of Latent Variable Training''. In Proceedings of Advances in Neural Information Processing Systems (NIPS-07).  [pdf]

  • Yuhong Guo and Dale Schuurmans (2007),  ``Discriminative Batch Mode Active Learning''. In Proceedings of Advances in Neural Information Processing Systems (NIPS-07).  [pdf]

  • Yuhong Guo and Dale Schuurmans (2007),  ``Learning Gene Regulatory Networks via Globally Regularized Risk Minimization''.  In Proceedings of the Fifth Annual RECOMB Satellite Workshop on Comparative Genomics (RECOMB-CG'07).  [pdf]

  • Yuhong Guo and Russ Greiner (2007),  ``Optimistic Active Learning using Mutual Information''.  In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI-07).  [pdf]

  • Yuhong Guo and Dale Schuurmans (2006),  ``Convex Structure Learning for Bayesian Networks: Polynomial Feature Selection and Approximate Ordering''.  In Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI-06).  [pdf]

  • Dale Schuurmans, Finnegan Southey, Dana Wilkinson and Yuhong Guo (2006),   ``Metric-based Approaches for Semi-supervised Regression and Classification''.   In O. Chapelle, B. Schoelkopf, and A. Zien, editors, Semi-Supervised Learning, MIT Press. [pdf]

  • Yuhong Guo, Russ Greiner and Dale Schuurmans (2005),   ``Learning Coordination Classifiers".   In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05).  (Distinguished Paper Award) [pdf]

  • Yuhong Guo, Dana Wilkinson and Dale Schuurmans (2005),  ``Maximum Margin Bayesian Networks''.  In Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI-05).  [pdf]

  • Yuhong Guo and Russ Greiner (2005),  ``Discriminative Model Selection for Belief Net Structures".  In Proceedings of the Twentieth AAAI Conference on Artificial Intelligence (AAAI-05).  [pdf]