Dongha Kim

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Demand Forecasting

Generative Model

Top Venues

Publications

Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Daniel K. Park
Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension. CoRR (2024)
Kwanyeob Chae, Jaegeun Song, Yoonjae Choi, Jiyeon Park, Billy Koo, Jihun Oh, Shinyoung Yi, Won Lee, Dongha Kim, Kyeongkeun Kang, Eunsu Kim, Juyoung Kim, Sanghune Park, Sungcheol Park, Mijung Noh, Hyo-Gyuem Rhew, Jongshin Shin
A 4-nm 1.15 TB/s HBM3 Interface With Resistor-Tuned Offset Calibration and In Situ Margin Detection. IEEE J. Solid State Circuits 59 (1) (2024)
Dongha Kim, Yongchan Choi, Kunwoong Kim, Ilsang Ohn, Yongdai Kim
IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples. AAAI (2024)
Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models. J. Mach. Learn. Res. 24 (2023)
Dongha Kim, Jaesung Hwang, Jongjin Lee, Kunwoong Kim, Yongdai Kim
ODIM: an efficient method to detect outliers via inlier-memorization effect of deep generative models. CoRR (2023)
Dongha Kim, Hokeun Kim
Poster Abstract: Securing Edge-Based Real-Time IoT Systems. SenSys (2023)
Yong-Uk Yoon, Dongha Kim, Jooyoung Lee, Byung Tae Oh, Jae-Gon Kim
An Efficient Multi-Scale Feature Compression With QP-Adaptive Feature Channel Truncation for Video Coding for Machines. IEEE Access 11 (2023)
Kwanyeob Chae, Jiyeon Park, Jaegeun Song, Billy Koo, Jihun Oh, Shinyoung Yi, Won Lee, Dongha Kim, Taekyung Yeo, Kyeongkeun Kang, Sangsoo Park, Eunsu Kim, Sukhyun Jung, Sanghune Park, Sungcheol Park, Mijung Noh, Hyo-Gyuem Rhew, Jongshin Shin
A 4nm 1.15TB/s HBM3 Interface with Resistor-Tuned Offset-Calibration and In-Situ Margin-Detection. ISSCC (2023)
Dongha Kim, Yeongbin Jo, Taekyung Kim, Hokeun Kim
SST v1.0.0 with C API: Pluggable security solution for the Internet of Things. SoftwareX 22 (2023)
Seungki Hong, Dongha Kim, Jaehyung Lee, Reum Oh, Changsik Yoo, Sang Joon Hwang, Jooyoung Lee
DSAC: Low-Cost Rowhammer Mitigation Using In-DRAM Stochastic and Approximate Counting Algorithm. CoRR (2023)
Byeong-Gil Jun, Dongha Kim, Marten Lohstroh, Hokeun Kim
Reliable Event Detection Using Time-Synchronized IoT Platforms. CPS-IoT Week Workshops (2023)
Youri Su, Sanghun Lee, Eunji Song, Dongha Kim, Jaeduk Han, Hokeun Kim
Energy-Efficient Bus Encoding Techniques for Next-Generation PAM-4 DRAM Interfaces. ICCD (2022)
Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim
Learning fair representation with a parametric integral probability metric. CoRR (2022)
Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim
Learning fair representation with a parametric integral probability metric. ICML (2022)
Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
A likelihood approach to nonparametric estimation of a singular distribution using deep generative models. CoRR (2021)
Dongha Kim, Yongdai Kim
Understanding Effects of Architecture Design to Invariance and Complexity in Deep Neural Networks. IEEE Access 9 (2021)
Yongdai Kim, Ilsang Ohn, Dongha Kim
Fast convergence rates of deep neural networks for classification. Neural Networks 138 (2021)
Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik
Kernel-convoluted Deep Neural Networks with Data Augmentation. AAAI (2021)
Dongha Kim, Yongchan Choi, Kunwoong Kim, Yongdai Kim
INN: A Method Identifying Clean-annotated Samples via Consistency Effect in Deep Neural Networks. CoRR (2021)
Dongha Kim, Jaesung Hwang, Yongdai Kim
On casting importance weighted autoencoder to an EM algorithm to learn deep generative models. AISTATS (2020)
Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik
Kernel-convoluted Deep Neural Networks with Data Augmentation. CoRR (2020)
Dongha Kim, JongRoul Woo, Jungwoo Shin, Jongsu Lee, Yongdai Kim
Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market. Ind. Manag. Data Syst. 119 (5) (2019)
Dongha Kim, Yongchan Choi, Yongdai Kim
Understanding and Improving Virtual Adversarial Training. CoRR (2019)
Yongdai Kim, Ilsang Ohn, Dongha Kim
Fast convergence rates of deep neural networks for classification. CoRR (2018)
Yongdai Kim, Dongha Kim
On variation of gradients of deep neural networks. CoRR (2018)