Publications Related to Data Mining

  1. Learning from Sets of Items in Recommender Systems.

    Mohit Sharma, F. Maxwell Harper, and George Karypis. 9th Intl. Conf. on Information, Process, and Knowledge Management (eKNOW), 2017.

  1. Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory.

    Shaden Smith, Jongsoo Park, and George Karypis. IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2017.

  1. Exploring Optimizations on Shared-memory Platforms for Parallel Triangle Counting Algorithms.

    Ancy Sarah Tom, Narayanan Sundaram, Nesreen K. Ahmed, Shaden Smith, Stijn Eyerman, Midhunchandra Kodiyath, Ibrahim Hur, Fabrizio Petrini, and George Karypis. IEEE High Performance Extreme Computing Conference (HPEC), 2017.

  1. Truss Decomposition on Shared-Memory Parallel Systems.

    Shaden Smith, Xing Liu, Nesreen K. Ahmed, Ancy Sarah Tom, Fabrizio Petrini, and George Karypis. IEEE High Performance Extreme Computing Conference (HPEC), 2017.

  1. Accelerating the Tucker Decomposition with Compressed Sparse Tensors.

    Shaden Smith and George Karypis. European Conference on Parallel Processing, 653-668, 2017.

  1. Constrained Tensor Factorization with Accelerated AO-ADMM.

    Shaden Smith, Alec Beri, and George Karypis. 46th International Conference on Parallel Processing (ICPP), 2017.

  1. Enriching Course-Specific Regression Models with Content Features for Grade Prediction.

    Qian Hu, Agoritsa Polyzou, George Karypis, and Huzefa Rangwala. IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2017.

  1. Context-Aware Recommendation-Based Learning Analytics Using Tensor and Coupled Matrix Factorization.

    Faisal M. Almutairi, Nicholas D. Sidiropoulos, and George Karypis. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. 11, NO. 5, 2017.

  1. Cumulative Knowledge-based Regression Models for Next-term Grade Prediction.

    Sara Morsy and George Karypis. SIAM Data Mining Conference (SDM), 2017.

  1. Grade Prediction with Course and Student Specifi c Models.

    Agoritsa Polyzou and George Karypis. International Journal of Data Science and Analytics, 2016.

  1. Fast Parallel Cosine K-Nearest Neighbor Graph Construction.

    David Anastasiu and George Karypis. 6th Workshop on Irregular applications: Architectures and Algorithms, Supercomputing, 2016.

  1. Predicting Student Performance Using Personalized Analytics.

    Asmaa Elbadrawy, Agoritsa Polyzou, Zhiyun Ren, Mackenzie Sweeney, George Karypis, and Huzefa Rangwala. IEEE Computer, pp. 61—69, April , 2016.