Mark Coletti

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 19

Top Topics

Autonomous Driving

Evolutionary Algorithm

Optimization Problems

Top Venues

GECCO Companion

Publications

Tyler J. Skluzacek, Renan Souza, Mark Coletti, Frédéric Suter, Rafael Ferreira da Silva
Towards Cross-Facility Workflows Orchestration through Distributed Automation. PEARC (2024)
Mark Coletti, Chathika Gunaratne, Steven R. Young, Swetha Varadarajan, Robert M. Patton, Thomas E. Potok
Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search. GECCO Companion (2024)
Prasanna Date, Chathika Gunaratne, Shruti R. Kulkarni, Robert M. Patton, Mark Coletti, Thomas E. Potok
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing. ICONS (2023)
Mark Coletti, Ada Sedova, Rajni Chahal, Luke Gibson, Santanu Roy, Vyacheslav Bryantsev
Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II. ICPP Workshops (2023)
Russell B. Davidson, Mark Coletti, Mu Gao, Bryan Piatkowski, Avinash Sreedasyam, Farhan Quadir, David J. Weston, Jeremy Schmutz, Jianlin Cheng, Jeffrey Skolnick, Jerry M. Parks, Ada Sedova
and proteome-scale annotation. Bioinform. 39 (8) (2023)
Prasanna Date, Chathika Gunaratne, Shruti Kulkarni, Robert M. Patton, Mark Coletti, Thomas E. Potok
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing. CoRR (2023)
Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Chathika Gunaratne, Kenneth A. De Jong
Avoiding excess computation in asynchronous evolutionary algorithms. Expert Syst. J. Knowl. Eng. 40 (5) (2023)
Mark Coletti, Chathika Gunaratne, Catherine D. Schuman, Robert M. Patton
Training reinforcement learning models via an adversarial evolutionary algorithm. ICPP Workshops (2022)
Robert M. Patton, Prasanna Date, Shruti R. Kulkarni, Chathika Gunaratne, Seung-Hwan Lim, Guojing Cong, Steven R. Young, Mark Coletti, Thomas E. Potok, Catherine D. Schuman
Neuromorphic Computing for Scientific Applications. RSDHA@SC (2022)
Mu Gao, Mark Coletti, Russell B. Davidson, Ryan Prout, Subil Abraham, Benjamín Hernández, Ada Sedova
Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer. IPDPS Workshops (2022)
Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC (2021)
Maryam Parsa, Shruti R. Kulkarni, Mark Coletti, Jeffrey K. Bassett, J. Parker Mitchell, Catherine D. Schuman
Multi-Objective Hyperparameter Optimization for Spiking Neural Network Neuroevolution. CEC (2021)
Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Kenneth A. De Jong
Avoiding Excess Computation in Asynchronous Evolutionary Algorithms. UKCI (2021)
Shang Gao, Spencer Paulissen, Mark Coletti, Robert M. Patton
Quantitative Evaluation of Autonomous Driving in CARLA. IV Workshops (2021)
Mark Coletti, Alex Fafard, David Page
Troubleshooting deep-learner training data problems using an evolutionary algorithm on Summit. IBM J. Res. Dev. 64 (3/4) (2020)
Mark Coletti, Eric O. Scott, Jeffrey K. Bassett
Library for evolutionary algorithms in Python (LEAP). GECCO Companion (2020)
Alexander J. Fafard, Jan van Aardt, Mark Coletti, David L. Page
Global Partitioning Elevation Normalization Applied to Building Footprint Prediction. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13 (2020)
Kuldeep R. Kurte, Jibonananda Sanyal, Anne Berres, Dalton D. Lunga, Mark Coletti, Hsiuhan Lexie Yang, Daniel Graves, Benjamin Liebersohn, Amy N. Rose
Performance analysis and optimization for scalable deployment of deep learning models for country-scale settlement mapping on Titan supercomputer. Concurr. Comput. Pract. Exp. 31 (20) (2019)
Mark Coletti, Dalton D. Lunga, Jeffrey K. Bassett, Amy N. Rose
Evolving Larger Convolutional Layer Kernel Sizes for a Settlement Detection Deep-Learner on Summit. DLS@SC (2019)
Mark Coletti
The effects of training set size and keeping rules on the emergent selection pressure of learnable evolution model. GECCO (Companion) (2012)
Mark Coletti, Guido Cervone
Analysis of Emergent Selection Pressure in Evolutionary Algorithm and Machine Learner Offspring Filtering Hybrids. SEMCCO (2012)
William G. Kennedy, Chenna Reddy Cotla, Tim Gulden, Mark Coletti, Claudio Cioffi-Revilla
Towards Validating a Model of Households and Societies in East Africa. WCSS (2012)
Michael Q. Kalish, Alexei V. Samsonovich, Mark Coletti, Kenneth A. De Jong
Assessing the Role of Metacognition in GMU BICA. BICA (2010)
Mark Coletti
Learnable evolution model performance impaired by binary tournament survival selection. GECCO (Companion) (2009)
Jeffrey K. Bassett, Mark Coletti, Kenneth A. De Jong
The relationship between evolvability and bloat. GECCO (2009)
Mark Coletti
A preliminary study of learnable evolution methodology implemented with C4.5. IEEE Congress on Evolutionary Computation (2002)
Mark Coletti, Thomas D. Lash, Ryszard S. Michalski, Craig Mandsager, Rida E. Moustafa
Comparing Performance of the Learnable Evolution Model and Genetic Algorithms. GECCO (1999)