Greg Hamerly

Orcid: 0000-0002-0360-1544

According to our database1, Greg Hamerly authored at least 28 papers between 2001 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Is ReLU Adversarially Robust?
CoRR, 2024

Active Learning Strategy Using Contrastive Learning and K-means for Aquatic Invasive Species Recognition.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2024

Using Annealing to Accelerate Triangle Inequality k-means.
Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

Beta k-Means: Accelerating k-Means Using Probabilistic Cluster Filtering.
Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

2023
Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer.
Proceedings of the Advances in Visual Computing - 18th International Symposium, 2023

2022
Recognition of Aquatic Invasive Species Larvae Using Autoencoder-Based Feature Averaging.
Proceedings of the Advances in Visual Computing - 17th International Symposium, 2022

Clustering Faster and Better with Projected Data.
Proceedings of the ICISDM 2022: 2022 the 6th International Conference on Information System and Data Mining, Silicon Valley, CA, USA, May 27, 2022

2016
Geometric methods to accelerate <i>k</i>-means algorithms.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

2014
Finding the smallest circle containing the iris in the denoised wavelet domain.
Proceedings of the 2014 Southwest Symposium on Image Analysis and Interpretation, 2014

A Convolutional Neural Network approach for classifying leukocoria.
Proceedings of the 2014 Southwest Symposium on Image Analysis and Interpretation, 2014

2010
Making k-means Even Faster.
Proceedings of the SIAM International Conference on Data Mining, 2010

Efficient Model Selection for Large-Scale Nearest-Neighbor Data Mining.
Proceedings of the Data Security and Security Data, 2010

2009
Hierarchical Stability-Based Model Selection for Clustering Algorithms.
Proceedings of the International Conference on Machine Learning and Applications, 2009

2007
Cross Binary Simulation Points.
Proceedings of the 2007 IEEE International Symposium on Performance Analysis of Systems and Software, 2007

2006
Using Machine Learning to Guide Architecture Simulation.
J. Mach. Learn. Res., 2006

PG-means: learning the number of clusters in data.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Comparing multinomial and k-means clustering for SimPoint.
Proceedings of the 2006 IEEE International Symposium on Performance Analysis of Systems and Software, 2006

2005
SimPoint 3.0: Faster and More Flexible Program Phase Analysis.
J. Instr. Level Parallelism, 2005

The Strong correlation Between Code Signatures and Performance.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2005

Motivation for Variable Length Intervals and Hierarchical Phase Behavior.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2005

2004
How to use SimPoint to pick simulation points.
SIGMETRICS Perform. Evaluation Rev., 2004

2003
Discovering and Exploiting Program Phases.
IEEE Micro, 2003

Using SimPoint for accurate and efficient simulation.
Proceedings of the International Conference on Measurements and Modeling of Computer Systems, 2003

Learning the k in k-means.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Picking Statistically Valid and Early Simulation Points.
Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques (PACT 2003), 27 September, 2003

2002
Alternatives to the k-means algorithm that find better clusterings.
Proceedings of the 2002 ACM CIKM International Conference on Information and Knowledge Management, 2002

Automatically characterizing large scale program behavior.
Proceedings of the 10th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-X), 2002

2001
Bayesian approaches to failure prediction for disk drives.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001


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