Complete list of publications

  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.

  1. Multi-task Learning for Recommender Systems.

    Xia Ning and George Karypis. 2nd Asian Conference on Machine Learning (ACML), 2010.

  1. Content-Based Methods for Predicting Web-Site Demographic Attributes.

    Santosh Kabbur, Eui-Hong Han, and George Karypis. 10th IEEE International Conference on Data Mining (ICDM), 2010.

  1. Assessing Synthetic Accessibility of Chemical Compounds Using Machine Learning Methods.

    Yevgeniy Podolyan, Michael Walters, and George Karypis. Journal of Chemical Information and Modeling, Vol. 50, pp. 979—991, 2010.