On variation of gradients of deep neural networks. - Yongdai Kim; Dongha Kim (CoRR, 2018)

Understanding and Improving Virtual Adversarial Training. - Dongha Kim; Yongchan Choi; Yongdai Kim (CoRR, 2019)

Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market. - Dongha Kim; JongRoul Woo; Jungwoo Shin; Jongsu Lee; Yongdai Kim (Ind. Manag. Data Syst., 2019)

On casting importance weighted autoencoder to an EM algorithm to learn deep generative models. - Dongha Kim; Jaesung Hwang; Yongdai Kim (AISTATS, 2020)

Kernel-convoluted Deep Neural Networks with Data Augmentation. - Minjin Kim; Young-geun Kim 002; Dongha Kim; Yongdai Kim; Myunghee Cho Paik (AAAI, 2021)

Understanding Effects of Architecture Design to Invariance and Complexity in Deep Neural Networks. - Dongha Kim; Yongdai Kim (IEEE Access, 2021)

INN: A Method Identifying Clean-annotated Samples via Consistency Effect in Deep Neural Networks. - Dongha Kim; Yongchan Choi; Kunwoong Kim; Yongdai Kim (CoRR, 2021)

Fast convergence rates of deep neural networks for classification. - Yongdai Kim; Ilsang Ohn; Dongha Kim (Neural Networks, 2021)

Energy-Efficient Bus Encoding Techniques for Next-Generation PAM-4 DRAM Interfaces. - Youri Su; Sanghun Lee; Eunji Song; Dongha Kim; Jaeduk Han; Hokeun Kim (ICCD, 2022)

Learning fair representation with a parametric integral probability metric. - Dongha Kim; Kunwoong Kim; Insung Kong; Ilsang Ohn; Yongdai Kim (ICML, 2022)

Reliable Event Detection Using Time-Synchronized IoT Platforms. - Byeong-Gil Jun; Dongha Kim; Marten Lohstroh; Hokeun Kim (CPS-IoT Week Workshops, 2023)

A 4nm 1.15TB/s HBM3 Interface with Resistor-Tuned Offset-Calibration and In-Situ Margin-Detection. - Kwanyeob Chae; Jiyeon Park; Jaegeun Song; Billy Koo; Jihun Oh; Shinyoung Yi 002; Won Lee; Dongha Kim; Taekyung Yeo; Kyeongkeun Kang; Sangsoo Park; Eunsu Kim; et al. (ISSCC, 2023)

Poster Abstract: Securing Edge-Based Real-Time IoT Systems. - Dongha Kim; Hokeun Kim (SenSys, 2023)

An Efficient Multi-Scale Feature Compression With QP-Adaptive Feature Channel Truncation for Video Coding for Machines. - Yong-Uk Yoon; Dongha Kim; Jooyoung Lee 004; Byung Tae Oh; Jae-Gon Kim (IEEE Access, 2023)

ODIM: an efficient method to detect outliers via inlier-memorization effect of deep generative models. - Dongha Kim; Jaesung Hwang; Jongjin Lee; Kunwoong Kim; Yongdai Kim (CoRR, 2023)

DSAC: Low-Cost Rowhammer Mitigation Using In-DRAM Stochastic and Approximate Counting Algorithm. - Seungki Hong; Dongha Kim; Jaehyung Lee; Reum Oh; Changsik Yoo; Sang Joon Hwang; Jooyoung Lee (CoRR, 2023)

A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models. - Minwoo Chae; Dongha Kim; Yongdai Kim; Lizhen Lin (J. Mach. Learn. Res., 2023)

SST v1.0.0 with C API: Pluggable security solution for the Internet of Things. - Dongha Kim; Yeongbin Jo; Taekyung Kim; Hokeun Kim (SoftwareX, 2023)

IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples. - Dongha Kim; Yongchan Choi; Kunwoong Kim; Ilsang Ohn; Yongdai Kim (AAAI, 2024)

Beyond Ontology in Dialogue State Tracking for Goal-Oriented Chatbot. - Sejin Lee; Dongha Kim; Min Song (ICKG, 2024)

ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models. - Dongha Kim; Jaesung Hwang; Jongjin Lee; Kunwoong Kim; Yongdai Kim (ICML, 2024)

Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension. - Changwon Lee; Israel F. Araujo; Dongha Kim; Junghan Lee; Siheon Park; Ju-Young Ryu; Daniel K. Park (CoRR, 2024)

META-ANOVA: Screening interactions for interpretable machine learning. - Yongchan Choi; Seokhun Park; Chanmoo Park; Dongha Kim; Yongdai Kim (CoRR, 2024)

Illustrious: an Open Advanced Illustration Model. - Sang Hyun Park; Jun Young Koh; Junha Lee; Joy Song; Dongha Kim; Hoyeon Moon; Hyunju Lee; Min Song (CoRR, 2024)

A Case Study of API Design for Interoperability and Security of the Internet of Things. - Dongha Kim; Chanhee Lee; Hokeun Kim (CoRR, 2024)

A 4-nm 1.15 TB/s HBM3 Interface With Resistor-Tuned Offset Calibration and In Situ Margin Detection. - Kwanyeob Chae; Jaegeun Song; Yoonjae Choi; Jiyeon Park; Billy Koo; Jihun Oh; Shinyoung Yi 002; Won Lee; Dongha Kim; Kyeongkeun Kang; Eunsu Kim; Juyoung Kim; et al. (IEEE J. Solid State Circuits, 2024)

Enhanced Wi-Fi Access Point Positioning Using Hexagonal CNN With Mobile Data and Urban Information. - Wonseo Choi; Dongha Kim; Sangmo Sung; Dohyung Han; Haeun Jo; Dongwook Choi; Jae-Il Jung; Hokeun Kim (IEEE Internet Things J., 2024)

ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect. - Seoyoung Cho; Jaesung Hwang; Kwan-Young Bak; Dongha Kim (AAAI, 2025)

Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph. - Deeksha Prahlad; Chanhee Lee; Dongha Kim; Hokeun Kim (WWW (Companion Volume), 2025)

Comparative Analysis of Ultraviolet Lamp Configurations in Large Chambers for Residual Contaminant Removal. - Dongha Kim; Seonghyun Park 006; Bokyung Jung; Janghoo Seo (IEEE Access, 2025)

SynC2S: An Efficient Method for Synthesizing Tabular Data With a Learnable Pre-Processing. - Jiwoo Kim; Seri Park; Junsung Koh; Dongha Kim (IEEE Access, 2025)

Four decades of data & knowledge engineering: A bibliometric analysis and topic evolution study (1985-2024). - Tatsawan Timakum; Soobin Lee; Dongha Kim; Min Song 001; Il-Yeol Song (Data Knowl. Eng., 2025)

SHIELD: Encrypting Persistent Data of LSM-KVS from Monolithic to Disaggregated Storage. - Viraj Thakkar; Dongha Kim; Yingchun Lai; Hokeun Kim; Zhichao Cao 002 (Proc. ACM Manag. Data, 2025)

MIRRAMS: Towards Training Models Robust to Missingness Distribution Shifts. - Jihye Lee; Minseo Kang; Dongha Kim (CoRR, 2025)

Federated Continual Recommendation. - Jaehyung Lim; Wonbin Kweon; Woojoo Kim; Junyoung Kim; Seongjin Choi; Dongha Kim; Hwanjo Yu (CoRR, 2025)