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2020 – today
- 2024
[c26]Shaif Chowdhury, Sadia Nasrin Tisha, Mushfika Rahman, Greg Hamerly:
Efficient Selective Pre-Training for Imbalanced Fine-Tuning Data in Transfer Learning. IEEE Big Data 2024: 6982-6991- [c25]Shaif Chowdhury, Aaron Carney, Greg Hamerly, Greg Speegle:
ACFed: Communication-Efficient & Class-Balancing Federated Learning with Adaptive Consensus Dropout & Model Quantization. IEEE Big Data 2024: 7707-7716 - [c24]Alibek Zhakubayev, Greg Hamerly:
Beta k-Means: Accelerating k-Means Using Probabilistic Cluster Filtering. DSAA 2024: 1-10 - [c23]Alibek Zhakubayev, Greg Hamerly:
Using Annealing to Accelerate Triangle Inequality k-means. DSAA 2024: 1-9 - [c22]Sadia Nasrin Tisha, Greg Hamerly:
Contrastive Learning for Detecting Invasive Aquatic Species: An Analysis of SimCLR and Self-Supervised Methods with Unlabeled Video Data. IVCNZ 2024: 1-6 - [c21]Shaif Chowdhury, Greg Hamerly, Monica E. McGarrity:
Active Learning Strategy Using Contrastive Learning and K-means for Aquatic Invasive Species Recognition. WACV (Workshops) 2024: 848-858 - [i1]Korn Sooksatra, Greg Hamerly, Pablo Rivas
:
Is ReLU Adversarially Robust? CoRR abs/2405.03777 (2024) - 2023
- [c20]Shaif Chowdhury, Sadia Nasrin Tisha, Monica E. McGarrity, Greg Hamerly:
Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer. ISVC (1) 2023: 224-235 - 2022
- [c19]Alibek Zhakubayev, Greg Hamerly:
Clustering Faster and Better with Projected Data. ICISDM 2022: 1-6 - [c18]Shaif Chowdhury, Greg Hamerly:
Recognition of Aquatic Invasive Species Larvae Using Autoencoder-Based Feature Averaging. ISVC (1) 2022: 145-161
2010 – 2019
- 2016
- [c17]Petr Rysavý, Greg Hamerly:
Geometric methods to accelerate k-means algorithms. SDM 2016: 324-332 - 2014
- [c16]Ryan Henning, Pablo Rivas-Perea, Bryan Shaw, Greg Hamerly:
A Convolutional Neural Network approach for classifying leukocoria. SSIAI 2014: 9-12 - [c15]Pablo Rivas-Perea, Ryan Henning, Bryan Shaw, Greg Hamerly:
Finding the smallest circle containing the iris in the denoised wavelet domain. SSIAI 2014: 13-16 - 2010
- [c14]Greg Hamerly, Greg Speegle:
Efficient Model Selection for Large-Scale Nearest-Neighbor Data Mining. BNCOD 2010: 37-54 - [c13]Greg Hamerly:
Making k-means Even Faster. SDM 2010: 130-140
2000 – 2009
- 2009
- [c12]Bing Yin, Greg Hamerly:
Hierarchical Stability-Based Model Selection for Clustering Algorithms. ICMLA 2009: 217-222 - 2007
- [c11]Erez Perelman, Jeremy Lau, Harish Patil, Aamer Jaleel, Greg Hamerly, Brad Calder:
Cross Binary Simulation Points. ISPASS 2007: 179-189 - 2006
- [j4]Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Calder, Timothy Sherwood:
Using Machine Learning to Guide Architecture Simulation. J. Mach. Learn. Res. 7: 343-378 (2006) - [c10]Greg Hamerly, Erez Perelman, Brad Calder:
Comparing multinomial and k-means clustering for SimPoint. ISPASS 2006: 131-142 - [c9]Yu Feng, Greg Hamerly:
PG-means: learning the number of clusters in data. NIPS 2006: 393-400 - 2005
- [j3]Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Calder:
SimPoint 3.0: Faster and More Flexible Program Phase Analysis. J. Instr. Level Parallelism 7 (2005) - [c8]Jeremy Lau, Erez Perelman, Greg Hamerly, Timothy Sherwood, Brad Calder:
Motivation for Variable Length Intervals and Hierarchical Phase Behavior. ISPASS 2005: 135-146 - [c7]Jeremy Lau, Jack Sampson, Erez Perelman, Greg Hamerly, Brad Calder:
The Strong correlation Between Code Signatures and Performance. ISPASS 2005: 236-247 - 2004
- [j2]Greg Hamerly, Erez Perelman, Brad Calder:
How to use SimPoint to pick simulation points. SIGMETRICS Perform. Evaluation Rev. 31(4): 25-30 (2004) - 2003
- [j1]Timothy Sherwood, Erez Perelman, Greg Hamerly, Suleyman Sair, Brad Calder:
Discovering and Exploiting Program Phases. IEEE Micro 23(6): 84-93 (2003) - [c6]Erez Perelman, Greg Hamerly, Brad Calder:
Picking Statistically Valid and Early Simulation Points. IEEE PACT 2003: 244-255 - [c5]Greg Hamerly, Charles Elkan:
Learning the k in k-means. NIPS 2003: 281-288 - [c4]Erez Perelman, Greg Hamerly, Michael Van Biesbrouck, Timothy Sherwood, Brad Calder:
Using SimPoint for accurate and efficient simulation. SIGMETRICS 2003: 318-319 - 2002
- [c3]Timothy Sherwood, Erez Perelman, Greg Hamerly, Brad Calder:
Automatically characterizing large scale program behavior. ASPLOS 2002: 45-57 - [c2]Greg Hamerly, Charles Elkan:
Alternatives to the k-means algorithm that find better clusterings. CIKM 2002: 600-607 - 2001
- [c1]Greg Hamerly, Charles Elkan:
Bayesian approaches to failure prediction for disk drives. ICML 2001: 202-209
Coauthor Index
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