CHU, WEI(褚崴)


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Representative Journal Articles  

Representative Conference Papers  

Natural Language Processing  

Computer Vision  

Recommender Systems  

Bioinformatics  

Machine Learning  


Representative Journal Articles

  1. W. Chu and S. S. Keerthi (2007)  Support vector ordinal regressionNeural Computation 19(3):792-815 (View Abstract)

  2. W. Chu, Z. Ghahramani, A. Podtelezhnikov and D. L. Wild (2006) Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map predictionIEEE/ACM Transactions on Computational Biology and Bioinformatics 3(2):98-113 (View Abstract)

  3. W. Chu and Z. Ghahramani (2005)  Gaussian processes for ordinal regression,  Journal of Machine Learning Research 6(Jul):1019-1041 (View Abstract)

  4. W. Chu, S. S. Keerthi and C. J. Ong (2004)  Bayesian support vector regression using a unified loss functionIEEE Transactions on Neural Networks 15(1):29-44 (View Abstract)

  5. W. Chu, S. S. Keerthi and C. J. Ong (2003)  Bayesian trigonometric support vector classifierNeural Computation 15(9):2227-2254 (View Abstract)


Representative Conference Papers

  1. W. Chu, M. Zinkevich, L. Li, A. Thomas, and B. Tseng (2011) Unbiased online active learning in data streams, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-17) (View Abstract)

  2. W. Chu, V. Sindhwani, Z. Ghahramani and S. S. Keerthi (2006) Relational learning with Gaussian processes, Neural Information Processing Systems (NIPS-19):289-296 (View Abstract)

  3. W. Chu and Z. Ghahramani (2005)  Preference learning with Gaussian processes, International Conference on Machine Learning (ICML-22):137-144 (View Abstract)

  4. W. Chu and S. S. Keerthi (2005)  New approaches to support vector ordinal regression,  International Conference on Machine Learning (ICML-22):145-152 (View Abstract)


Natural Language Processing Papers

  1. L. Chao, J. He, T. Wang and W. Chu (2021) PairRE: Knowledge graph embeddings via paired relation vectors, ACL 2021: 4360-4369 (View Abstract)

  2. K. Chen, W. Xu, X. Cheng, X. Zou, Y. Zhang, L. Song, T. Wang, Y. Qi and W. Chu (2020) Question directed graph attention network for numerical reasoning over text, EMNLP 2020:6759-6768 (View Abstract)

  3. X. Chen, W. Xu, K. Chen, T. Wang, S. Jiang, F. Wang, W. Chu and Y. Qi (2020) SpellGCN: Incorporating phonological and visual similarities into language models for Chinese Spelling Check, ACL 2020:871–881 (View Abstract)

  4. X. Lin, W. Jian, J. He, T. Wang, and W. Chu (2020) Generating informative conversational response using recurrent knowledge-interaction and knowledge-copy, ACL 2020:41–52 (View Abstract)

  5. M. Qiu, et al. (2017) AliMe Chat: a sequence to sequence and rerank based ChatBot engine, Annual Meeting of the Association for Computational Linguistics (ACL-55 Short Paper) (View Abstract)


Computer Vision Papers

  1. W. Hong, J. Lao, W. Ren, J. Wang, J. Chen, W. Chu (2022) Training Object Detectors from Scratch: An Empirical Study in the Era of Vision Transformer, in Proc. of CVPR 2022 (View Abstract)

  2. F. Xu, M. Wang, W. Zhang, Y. Cheng and W. Chu (2021) Discrimination-aware mechanism for fine-grained representation learning, CVPR 2021 (View Abstract)

  3. W. Hong, P. Guo, W. Zhang, J. Chen and W. Chu (2021) LPSNet: A lightweight solution for fast panoptic segmentation, CVPR 2021 (View Abstract)

  4. C. Jiang, K. Huang, S. He, X. Yang, W. Zhang, X. Zhang, Y. Cheng, L. Yang, Q. Wang, F. Xu, T. Pan and W. Chu (2021) Learning segment similarity and alignment in large-scale content based video retrieval, ACM MM 2021 (View Abstract)


Recommender Systems Papers

  1. L. Li, W. Chu, J. Langford and X. Wang (2011) Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms, ACM International Conference on Web Search and Data Mining (WSDM-04) 297-306 (View Abstract)

  2. L. Li, W. Chu, J. Langford and R. E. Schapire (2010) A contextual-bandit approach to personalized news article recommendation, International World Wide Web Conference (WWW-19) 661-670 (View Abstract)

  3. S.-T. Park and W. Chu (2009) Pairwise preference regression for cold-start recommendation, ACM Recommender Systems (RecSys-03):21-28 (View Abstract)

  4. W. Chu and S.-T. Park (2009) Personalized recommendation on dynamic content using predictive bilinear models, International World Wide Web Conference (WWW-18):692-700 (View Abstract)


Bioinformatics Papers

  1. W. Chu, Z. Ghahramani, R. Krause and D. L. Wild  (2006)  Identifying protein complexes in high-throughput protein interaction screens using an infinite latent feature modelPacific Symposium on Biocomputing (PSB-11):231-242 (View Abstract)

  2. W. Chu, Z. Ghahramani, F. Falciani and D. L. Wild (2005)  Biomarker discovery with Gaussian processes in microarray gene expression data,  Bioinformatics 2005(21):3385-3393 (View Abstract)

  3. W. Chu, Z. Ghahramani and D. L. Wild (2004)  A graphical model for protein secondary structure prediction,  International Conference on Machine Learning (ICML-21):161-168 (View Abstract)


Machine Learning Papers

  1. W. Chu, L. Li, L. Reyzin, and R. E. Schapire (2011) Contextual bandits with linear payoff functions, International Conference on Artificial Intelligence and Statistics (AISTATS-14) (View Abstract)

  2. W. Chu and Z. Ghahramani (2009) Probabilistic models for incomplete multi-dimensional arrays, International Conference on Artificial Intelligence and Statistics (AISTATS-12):89-96 (View Abstract)

  3. R. Silva, W. Chu and Z. Ghahramani (2007) Hidden common cause relations in relational learning, Neural Information Processing Systems (NIPS-20):1345-1352 (View Abstract)

  4. K. Yu and W. Chu (2007) Gaussian process models for link analysis and transfer learning, Neural Information Processing Systems (NIPS-20):1657-1664 (View Abstract)

  5. P. K. Shivaswamy, W. Chu and M. Jansche (2007) A support vector approach to censored targets, IEEE International Conference on Data Mining (ICDM-07):655-660 (View Abstract)

  6. V. Sindhwani, W. Chu and S. S. Keerthi (2007) Semi-supervised Gaussian process classifiersInternational Joint Conferences on Artificial Intelligence (IJCAI-20):1059-1064 (View Abstract)

  7. K. Yu, W. Chu, S. Yu, V. Tresp and Z. Xu (2006) Stochastic relational models for discriminative link prediction, Neural Information Processing Systems (NIPS-19):1553-1560 (View Abstract)

  8. S. K. Shevade and W. Chu (2006) Minimum enclosing spheres formulations for support vector ordinal regressionIEEE International Conference on Data Mining (ICDM-06):1054-1058 (View Abstract)

  9. W. Chu, C. J. Ong and S. S. Keerthi (2005)  An improved conjugate gradient scheme to the solution of least squares SVM,  IEEE Transactions on Neural Networks 16(2):498-501 (View Abstract)

  10. S. S. Keerthi and W. Chu (2005)  A matching pursuit approach to sparse Gaussian process regression, Neural Information Processing Systems (NIPS-18):643-650 (View Abstract)

  11. W. Chu and Z. Ghahramani (2005)  Extensions of Gaussian processes for ranking: semi-supervised and active learningWorkshop Learning to Rank at (NIPS-18):29-34 (View Abstract)

  12. W. Chu, S. S. Keerthi and C. J. Ong (2001)  A unified loss function in Bayesian framework for support vector regression,  International Conference on Machine Learning (ICML-18):51-58


EMAIL : email dot chuwei at gmail.com

2022.03.09