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George Karypis

1970 …2023
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Projects 2004 2023

Collaborative Research: Reliable Materials Simulation based on the Knowledgebase of Interatomic Models (KIM)

Tadmor, E. B., Elliott, R. S. & Karypis, G.

National Science Foundation

10/1/18 → 9/30/22

Project: Research project

simulation

REU Site: Computational Methods for Discovery Driven by

Karypis, G., Jensen, K. & Larson, A. C.

National Science Foundation

4/1/18 → 3/31/21

Project: Research project

Computational methods
Big data

University of Minnesota Clinical and Translational Scien

Blazar, B. R., AbuSalah, A. M., Adam, T. J., Aliferis, MD, PhD, C., Allen, J. R., Beckman, K. B., Billings, J. L., Bloomfield, H. E., Bornsztein, B., Brearley, A. M., Call, K. T., Chi, C., Clancy, T. R., Connett, J. E., Daniels, B. S., Eder, M., El-Fakahany, E. E., Fischer, G., Fulkerson, J., Garwood, M., Georgopoulos, A. P., Guan, W., Henderson, J. N., Hodges, J. S., Ingbar, D. H., Jones-Webb, R. J., Jordan, C. M., Karypis, G., Knights, D., Kumar, V., LeBien, T. W., Lim, K. O., Ma, S., Melton-Meaux, G. B., Myers, C. L., Neuhauser, C., Oakes, M., Okuyemi, K., Pakhomov, S. V., Panoskaltsis-Mortari, A., Pieczkiewicz, D. S., Raymond, N. C., Riggs, S., Rudser, K., Ruggles, S., Schacker, T. W., Schleiss, M. R., Shekhar, S., Shen, S., Simon, G. J., Ugurbil, K., Vock, D. M., Volkov, B. B., Wang, J., Warren, J. R., Weber-Main, A. M., Weisdorf, D. J., Wolf, S. M., Zellmer-Bruhn, M. E. & Zhang, R.

NIH NAT'L CTR FOR ADVANCING TRAN SCIENCE

3/30/18 → 2/28/23

Project: Research project

science

Hierarchical Identify Verify Exploit (HIVE)

Karypis, G.

Intel Corporation

11/21/17 → 6/30/19

Project: Research project

III: Medium: High-Performance Factorization Tools for Co

Karypis, G. & Sidiropoulos, N.

National Science Foundation

9/1/17 → 8/31/21

Project: Research project

Research Output 1970 2018

A virtual memory manager optimized for node-level cooperative multi-tasking in memory constrained systems

Iverson, J. & Karypis, G., Sep 1 2018, In : International Journal of High Performance Computing Applications. 32, 5, p. 744-759 16 p.

Research output: Contribution to journal › Article

Virtual Memory
Multitasking
Constrained Systems
Managers
Message passing

Detecting significant genotype–phenotype association rules in bipolar disorder: market research meets complex genetics

Breuer, R., Mattheisen, M., Frank, J., Krumm, B., Treutlein, J., Kassem, L., Strohmaier, J., Herms, S., Mühleisen, T. W., Degenhardt, F., Cichon, S., Nöthen, M. M., Karypis, G., Kelsoe, J., Greenwood, T., Nievergelt, C., Shilling, P., Shekhtman, T., Edenberg, H., Craig, D. & 32 othersSzelinger, S., Nurnberger, J., Gershon, E., Alliey-Rodriguez, N., Zandi, P., Goes, F., Schork, N., Smith, E., Koller, D., Zhang, P., Badner, J., Berrettini, W., Bloss, C., Byerley, W., Coryell, W., Foroud, T., Guo, Y., Hipolito, M., Keating, B., Lawson, W., Liu, C., Mahon, P., McInnis, M., Murray, S., Nwulia, E., Potash, J., Rice, J., Scheftner, W., Zöllner, S., McMahon, F. J., Rietschel, M. & Schulze, T. G., Dec 1 2018, In : International Journal of Bipolar Disorders. 6, 1, 24.

Research output: Contribution to journal › Article

Genetic Association Studies
Marketing
Bipolar Disorder
Genome-Wide Association Study
Phenotype

Distributed representation of multi-sense words: A loss driven approach

Manchanda, S. & Karypis, G., Jan 1 2018, Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings. Ho, B., Phung, D., Webb, G. I., Tseng, V. S., Ganji, M. & Rashidi, L. (eds.). Springer- Verlag, p. 337-349 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10938 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Assign
Model
Experiment
Experiments
Similarity
2 Citations

Enriching course-Specific regression models with content features for grade prediction

Hu, Q., Polyzou, A., Karypis, G. & Rangwala, H., Jan 16 2018, Proceedings - 2017 International Conference on Data Science and Advanced Analytics, DSAA 2017. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-January. p. 504-513 10 p.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Regression Model
Students
Prediction
Flexibility
Pedagogy

HPC formulations of optimization algorithms for tensor completion

Smith, S., Park, J. & Karypis, G., May 1 2018, In : Parallel Computing. 74, p. 99-117 19 p.

Research output: Contribution to journal › Article

Alternating Least Squares
Charge coupled devices
Tensors
Completion
Optimization Algorithm

Datasets

Regions of High Confidence in Chinese Hamster and CHO-K1 Genome Assemblies

Bandyopadhyay, A. (Creator), Fu, H. (Creator), Hu, W. (Creator), Jacob, N. M. (Creator), Johnson, K. (Creator), Karypis, G. (Creator), Le, H. (Creator), Mudge, J. (Creator), Onsongo, G. (Creator), Ramaraj, T. (Creator), Sharma, M. (Creator), Silverstein, K. A. (Creator), Vishwanathan, N. (Creator), Data Repository for the University of Minnesota, 2016

DOI: 10.13020/D6Z304, http://dx.doi.org/10.13020/D6Z304

Dataset