Jaehoon Koo

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 16

Top Topics

Recurrent Neural Networks

Marginal Distributions

Reinforcement Learning

Top Venues

Publications

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 (2024)
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)
Xingfu Wu, Prasanna Balaprakash, Michael Kruse, Jaehoon Koo, Brice Videau, Paul D. Hovland, Valerie E. Taylor, Brad Geltz, Siddhartha Jana, Mary W. Hall
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales. CoRR (2023)
Jaehoon Koo, Diego Klabjan, Jean Utke
An inverse classification framework with limited budget and maximum number of perturbed samples. Expert Syst. Appl. 212 (2023)
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)
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 (2022)
Jaehoon Koo, Sangheum Hwang
A Unified Defect Pattern Analysis of Wafer Maps Using Density-Based Clustering. IEEE Access 9 (2021)
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)
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 (2021)
Jaehoon Koo, Diego Klabjan
Improved Classification Based on Deep Belief Networks. ICANN (1) (2020)
Jaehoon Koo, Diego Klabjan, Jean Utke
Combined Convolutional and Recurrent Neural Networks for Hierarchical Classification of Images. IEEE BigData (2020)
Jaehoon Koo, Diego Klabjan, Jean Utke
Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples. CoRR (2020)
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 (2019)
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)
Jaehoon Koo, Diego Klabjan
Improved Classification Based on Deep Belief Networks. CoRR (2018)
Jaehoon Koo, Diego Klabjan, Jean Utke
Combined convolutional and recurrent neural networks for hierarchical classification of images. CoRR (2018)
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) (2002)
Nirmal K. Bose, Surapong Lertrattanapanich, Jaehoon Koo
Advances in superresolution using L-curve. ISCAS (2) (2001)