Complete list of publications

  1. Function Genomics of Nectar Production in Brassicaceae.

    R. Bender, P. Klinkenberg, Z. Jiang, B. Bauer, G. Karypis, N. Nguyen, M. Perera, B. Nikolau, and C. Carter. Flora: Morphology, Distribution, Functional Ecology of Plants Volume 207, Issue 7, pp. 491-496, 2012.

  1. Multi-view learning via probabilistic latent semantic analysis .

    Fuzhen Zhuang, George Karypis, Xia Ning, Qing He, and Zhongzhi Shi. Information Sciences, 199; pp. 20-30, 2012.

  1. Improved Machine Learning Models for Predicting Selective Compounds.

    Xia Ning and George Karypis. Journal of Chemical Information and Modeling, 58, pp. 38-50, 2012.

  1. Sparse Linear Methods with Side Information for Top-N Recommendations.

    Xia Ning and George Karypis. 6th ACM Recommender Systems Conference (RecSys), 2012.

  1. Fast & Effective Lossy Compression Algorithms for Scientific Datasets.

    Jeremy Iverson, Chandrika Kamath, and George Karypis. Europar, 2012.

  1. Computational Tools for Protein-DNA Interactions.

    Chris Kauffman and George Karypis. WIREs Data Mining and Knowledge Discovery, 2(1): 14-28, 2012.

  1. SLIM: Sparse Linear Methods for Top-N Recommender Systems.

    Xia Ning and George Karypis. ICDM , 2011.

  1. Improved Machine Learning Models for Predicting Selective Compounds.

    Xia Ning, Michael Walters, and George Karypis. ACM Conference on Bioinformatics, Computational Biology and Biomedicine. Chicago, 2011.

  1. Automatic Detection of Vaccine Adverse Reactions by Incorporating Historical Medical Conditions.

    Zhonghua Jiang and George Karypis. ACM Conference on Bioinformatics, Computational Biology and Biomedicine. Chicago, 2011.

  1. In Silico Structure-Activity-Relationship (SAR) Models From Machine Learning: A Review.

    Xia Ning and George Karypis. Drug Development Research, Vol. 72, 2011.

  1. A Comprehensive Survey of Neighborhood-based Recommendation Methods.

    Christian Desrosiers and George Karypis. Recommender Systems Handbook, pp. 107-144, 2011.