Bayesian approaches to failure prediction for disk drives. - Greg Hamerly; Charles Elkan (ICML, 2001)

Automatically characterizing large scale program behavior. - Timothy Sherwood; Erez Perelman; Greg Hamerly; Brad Calder (ASPLOS, 2002)

Alternatives to the k-means algorithm that find better clusterings. - Greg Hamerly; Charles Elkan (CIKM, 2002)

Picking Statistically Valid and Early Simulation Points. - Erez Perelman; Greg Hamerly; Brad Calder (IEEE PACT, 2003)

Learning the k in k-means. - Greg Hamerly; Charles Elkan (NIPS, 2003)

Using SimPoint for accurate and efficient simulation. - Erez Perelman; Greg Hamerly; Michael Van Biesbrouck; Timothy Sherwood; Brad Calder (SIGMETRICS, 2003)

Discovering and Exploiting Program Phases. - Timothy Sherwood; Erez Perelman; Greg Hamerly; Suleyman Sair; Brad Calder (IEEE Micro, 2003)

How to use SimPoint to pick simulation points. - Greg Hamerly; Erez Perelman; Brad Calder (SIGMETRICS Perform. Evaluation Rev., 2004)

Motivation for Variable Length Intervals and Hierarchical Phase Behavior. - Jeremy Lau; Erez Perelman; Greg Hamerly; Timothy Sherwood; Brad Calder (ISPASS, 2005)

The Strong correlation Between Code Signatures and Performance. - Jeremy Lau; Jack Sampson; Erez Perelman; Greg Hamerly; Brad Calder (ISPASS, 2005)

SimPoint 3.0: Faster and More Flexible Program Phase Analysis. - Greg Hamerly; Erez Perelman; Jeremy Lau; Brad Calder (J. Instr. Level Parallelism, 2005)

Comparing multinomial and k-means clustering for SimPoint. - Greg Hamerly; Erez Perelman; Brad Calder (ISPASS, 2006)

PG-means: learning the number of clusters in data. - Yu Feng; Greg Hamerly (NIPS, 2006)

Using Machine Learning to Guide Architecture Simulation. - Greg Hamerly; Erez Perelman; Jeremy Lau; Brad Calder; Timothy Sherwood (J. Mach. Learn. Res., 2006)

Cross Binary Simulation Points. - Erez Perelman; Jeremy Lau; Harish Patil; Aamer Jaleel; Greg Hamerly; Brad Calder (ISPASS, 2007)

Hierarchical Stability-Based Model Selection for Clustering Algorithms. - Bing Yin; Greg Hamerly (ICMLA, 2009)

Efficient Model Selection for Large-Scale Nearest-Neighbor Data Mining. - Greg Hamerly; Greg Speegle (BNCOD, 2010)

Making k-means Even Faster. - Greg Hamerly (SDM, 2010)

A Convolutional Neural Network approach for classifying leukocoria. - Ryan Henning; Pablo Rivas-Perea; Bryan Shaw; Greg Hamerly (SSIAI, 2014)

Finding the smallest circle containing the iris in the denoised wavelet domain. - Pablo Rivas-Perea; Ryan Henning; Bryan Shaw; Greg Hamerly (SSIAI, 2014)

Geometric methods to accelerate k-means algorithms. - Petr Rysavý; Greg Hamerly (SDM, 2016)

Clustering Faster and Better with Projected Data. - Alibek Zhakubayev; Greg Hamerly (ICISDM, 2022)

Recognition of Aquatic Invasive Species Larvae Using Autoencoder-Based Feature Averaging. - Shaif Chowdhury; Greg Hamerly (ISVC (1), 2022)

Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer. - Shaif Chowdhury; Sadia Nasrin Tisha; Monica E. McGarrity; Greg Hamerly (ISVC (1), 2023)

ACFed: Communication-Efficient & Class-Balancing Federated Learning with Adaptive Consensus Dropout & Model Quantization. - Shaif Chowdhury; Aaron Carney; Greg Hamerly; Greg Speegle (IEEE Big Data, 2024)

Efficient Selective Pre-Training for Imbalanced Fine-Tuning Data in Transfer Learning. - Shaif Chowdhury; Sadia Nasrin Tisha; Mushfika Rahman; Greg Hamerly (IEEE Big Data, 2024)

Beta k-Means: Accelerating k-Means Using Probabilistic Cluster Filtering. - Alibek Zhakubayev; Greg Hamerly (DSAA, 2024)

Using Annealing to Accelerate Triangle Inequality k-means. - Alibek Zhakubayev; Greg Hamerly (DSAA, 2024)

Contrastive Learning for Detecting Invasive Aquatic Species: An Analysis of SimCLR and Self-Supervised Methods with Unlabeled Video Data. - Sadia Nasrin Tisha; Greg Hamerly (IVCNZ, 2024)

Active Learning Strategy Using Contrastive Learning and K-means for Aquatic Invasive Species Recognition. - Shaif Chowdhury; Greg Hamerly; Monica E. McGarrity (WACV (Workshops), 2024)

Is ReLU Adversarially Robust? - Korn Sooksatra; Greg Hamerly; Pablo Rivas 001 (CoRR, 2024)

Learning to Plan via Supervised Contrastive Learning and Strategic Interpolation: A Chess Case Study. - Andrew Hamara; Greg Hamerly; Pablo Rivas 001; Andrew C. Freeman (CoRR, 2025)