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Greg Hamerly
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Automatically characterizing large scale program behavior
T Sherwood, E Perelman, G Hamerly, B Calder
ACM SIGPLAN Notices 37 (10), 45-57, 2002
22532002
Learning the k in k-means
G Hamerly, C Elkan
Advances in neural information processing systems 16: proceedings of the …, 2004
13632004
Alternatives to the k-means algorithm that find better clusterings
G Hamerly, C Elkan
Proceedings of the eleventh international conference on Information and …, 2002
7782002
Simpoint 3.0: Faster and more flexible program phase analysis
G Hamerly, E Perelman, J Lau, B Calder
Journal of Instruction Level Parallelism 7 (4), 1-28, 2005
4862005
Using simpoint for accurate and efficient simulation
E Perelman, G Hamerly, M Van Biesbrouck, T Sherwood, B Calder
ACM SIGMETRICS Performance Evaluation Review 31 (1), 318-319, 2003
4512003
Discovering and exploiting program phases
T Sherwood, E Perelman, G Hamerly, S Sair, B Calder
IEEE micro 23 (6), 84-93, 2003
3752003
Picking statistically valid and early simulation points
E Perelman, G Hamerly, B Calder
2003 12th International Conference on Parallel Architectures and Compilation …, 2003
3172003
Bayesian approaches to failure prediction for disk drives
G Hamerly, C Elkan
ICML 1 (2001), 202-209, 2001
3032001
Making k-means even faster
G Hamerly
Proceedings of the 2010 SIAM international conference on data mining, 130-140, 2010
2652010
Accelerating Lloyd’s Algorithm for k-Means Clustering
G Hamerly, J Drake
Partitional clustering algorithms, 41-78, 2015
1612015
PG-means: learning the number of clusters in data
Y Feng, G Hamerly
Advances in Neural Information Processing Systems 19: Proceedings of the …, 2007
1362007
The strong correlation between code signatures and performance
J Lau, J Sampson, E Perelman, G Hamerly, B Calder
IEEE International Symposium on Performance Analysis of Systems and Software …, 2005
1222005
Accelerated k-means with adaptive distance bounds
J Drake, G Hamerly
5th NIPS workshop on optimization for machine learning 8, 1-4, 2012
1212012
Motivation for variable length intervals and hierarchical phase behavior
J Lau, E Perelman, G Hamerly, T Sherwood, B Calder
IEEE International Symposium on Performance Analysis of Systems and Software …, 2005
1012005
How to use simpoint to pick simulation points
G Hamerly, E Perelman, B Calder
ACM SIGMETRICS Performance Evaluation Review 31 (4), 25-30, 2004
992004
Using machine learning to guide architecture simulation.
G Hamerly, E Perelman, J Lau, B Calder, T Sherwood, H Hirsh
Journal of Machine Learning Research 7 (2), 2006
402006
Autonomous early detection of eye disease in childhood photographs
MC Munson, DL Plewman, KM Baumer, R Henning, CT Zahler, ...
Science advances 5 (10), eaax6363, 2019
342019
Detection of leukocoria using a soft fusion of expert classifiers under non-clinical settings
P Rivas-Perea, E Baker, G Hamerly, BF Shaw
BMC ophthalmology 14, 1-15, 2014
302014
Cross binary simulation points
E Perelman, J Lau, H Patil, A Jaleel, G Hamerly, B Calder
2007 IEEE International Symposium on Performance Analysis of Systems …, 2007
232007
A convolutional neural network approach for classifying leukocoria
R Henning, P Rivas-Perea, B Shaw, G Hamerly
2014 southwest symposium on image analysis and interpretation, 9-12, 2014
192014
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