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Jaehoon Koo
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2020 – today
- 2024
- [i8]Thomas Randall, Jaehoon Koo, Brice Videau, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall, Rong Ge, Prasanna Balaprakash:
Transfer-Learning-Based Autotuning Using Gaussian Copula. CoRR abs/2401.04669 (2024) - 2023
- [j3]Jaehoon Koo, Diego Klabjan, Jean Utke:
An inverse classification framework with limited budget and maximum number of perturbed samples. Expert Syst. Appl. 212: 118761 (2023) - [c7]Thomas Randall, Jaehoon Koo, Brice Videau, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall, Rong Ge, Prasanna Balaprakash:
Transfer-learning-based Autotuning using Gaussian Copula. ICS 2023: 37-49 - [i7]Xingfu Wu, Prasanna Balaprakash, Michael Kruse, Jaehoon Koo, Brice Videau, Paul D. Hovland, Valerie Taylor, Brad Geltz, Siddhartha Jana, Mary W. Hall:
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales. CoRR abs/2303.16245 (2023) - 2022
- [c6]Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy, Srinivasan Ramesh, Allen D. Malony, Robert B. Ross:
HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization. CLUSTER 2022: 381-393 - [i6]Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy, Srinivasan Ramesh, Allen D. Malony, Robert B. Ross:
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization. CoRR abs/2210.00798 (2022) - 2021
- [j2]Jaehoon Koo, Sangheum Hwang:
A Unified Defect Pattern Analysis of Wafer Maps Using Density-Based Clustering. IEEE Access 9: 78873-78882 (2021) - [c5]Jaehoon Koo, Prasanna Balaprakash, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall:
Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations. PMBS 2021: 82-93 - [i5]Jaehoon Koo, Prasanna Balaprakash, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall:
Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations. CoRR abs/2105.04555 (2021) - 2020
- [c4]Jaehoon Koo, Diego Klabjan, Jean Utke:
Combined Convolutional and Recurrent Neural Networks for Hierarchical Classification of Images. IEEE BigData 2020: 1354-1361 - [c3]Jaehoon Koo, Diego Klabjan:
Improved Classification Based on Deep Belief Networks. ICANN (1) 2020: 541-552 - [i4]Jaehoon Koo, Diego Klabjan, Jean Utke:
Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples. CoRR abs/2009.14111 (2020)
2010 – 2019
- 2019
- [c2]Jaehoon Koo, Veena B. Mendiratta, Muntasir Raihan Rahman, Anwar Walid:
Deep Reinforcement Learning for Network Slicing with Heterogeneous Resource Requirements and Time Varying Traffic Dynamics. CNSM 2019: 1-5 - [i3]Jaehoon Koo, Veena B. Mendiratta, Muntasir Raihan Rahman, Anwar Walid:
Deep Reinforcement Learning for Network Slicing with Heterogeneous Resource Requirements and Time Varying Traffic Dynamics. CoRR abs/1908.03242 (2019) - 2018
- [i2]Jaehoon Koo, Diego Klabjan:
Improved Classification Based on Deep Belief Networks. CoRR abs/1804.09812 (2018) - [i1]Jaehoon Koo, Diego Klabjan, Jean Utke:
Combined convolutional and recurrent neural networks for hierarchical classification of images. CoRR abs/1809.09574 (2018)
2000 – 2009
- 2002
- [j1]Michael K. Ng, Jaehoon Koo, Nirmal K. Bose:
Constrained total least-squares computations for high-resolution image reconstruction with multisensors. Int. J. Imaging Syst. Technol. 12(1): 35-42 (2002) - 2001
- [c1]Nirmal K. Bose, Surapong Lertrattanapanich, Jaehoon Koo:
Advances in superresolution using L-curve. ISCAS (2) 2001: 433-436
Coauthor Index
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