TSV optimization for BEOL interconnection in logic process. - Sinwoo Kang; Sungdong Cho; Kiyoung Yun; Sangwook Ji; Kisoon Bae; Woonseob Lee; Eunji Kim; Jangho Kim; Jonghoon Cho; Hyongyol Mun; Yeong L. Park (3DIC, 2011)

Code Optimization on Kepler GPUs and Xeon Phi. - Yong-Chull Jang; Hwancheol Jeong; Jangho Kim; Weonjong Lee; Jeonghwan Pak; Yuree Chung (CoRR, 2014)

Detecting Korean characters in natural scenes by alphabet detection and agglomerative character construction. - Jangho Kim; Yong-Joong Kim; Yonghyun Kim; Daijin Kim 001 (SMC, 2016)

Paraphrasing Complex Network: Network Compression via Factor Transfer. - Jangho Kim; Seonguk Park; Nojun Kwak (NeurIPS, 2018)

Generating objects going well with the surroundings. - Jeesoo Kim; Jaeyoung Yoo; Jangho Kim; Nojun Kwak (CoRR, 2018)

HC-Net: Memory-based Incremental Dual-Network System for Continual learning. - Jangho Kim; Jeesoo Kim; Nojun Kwak (CoRR, 2018)

QKD: Quantization-aware Knowledge Distillation. - Jangho Kim; Yash Bhalgat; Jinwon Lee; Chirag Patel; Nojun Kwak (CoRR, 2019)

StackNet: Stacking feature maps for Continual learning. - Jangho Kim; Jeesoo Kim; Nojun Kwak (CVPR Workshops, 2020)

Feature-map-level Online Adversarial Knowledge Distillation. - Inseop Chung; Seonguk Park; Jangho Kim; Nojun Kwak (ICML, 2020)

Feature Fusion for Online Mutual Knowledge Distillation. - Jangho Kim; Minsung Hyun; Inseop Chung; Nojun Kwak (ICPR, 2020)

Position-based Scaled Gradient for Model Quantization and Pruning. - Jangho Kim; KiYoon Yoo; Nojun Kwak (NeurIPS, 2020)

Position-based Scaled Gradient for Model Quantization and Sparse Training. - Jangho Kim; KiYoon Yoo; Nojun Kwak (CoRR, 2020)

Domain Generalization on Efficient Acoustic Scene Classification Using Residual Normalization. - Byeonggeun Kim; Seunghan Yang; Jangho Kim; Simyung Chang (DCASE, 2021)

Prototype-Based Personalized Pruning. - Jangho Kim; Simyung Chang; Sungrack Yun; Nojun Kwak (ICASSP, 2021)

Vehicle Image Generation Going Well with the Surroundings. - Jeesoo Kim; Jangho Kim; Jaeyoung Yoo; Daesik Kim; Nojun Kwak (ICONIP (4), 2021)

PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation. - Jangho Kim; Simyung Chang; Nojun Kwak (Interspeech, 2021)

Dynamic Collective Intelligence Learning: Finding Efficient Sparse Model via Refined Gradients for Pruned Weights. - Jangho Kim; Jayeon Yoo; Yeji Song; KiYoon Yoo; Nojun Kwak (CoRR, 2021)

Self-Distilled Self-Supervised Representation Learning. - Jiho Jang; Seonhoon Kim; KiYoon Yoo; Jangho Kim; Nojun Kwak (CoRR, 2021)

Detection of Adversarial Examples in Text Classification: Benchmark and Baseline via Robust Density Estimation. - KiYoon Yoo; Jangho Kim; Jiho Jang; Nojun Kwak (ACL (Findings), 2022)

Variational On-the-Fly Personalization. - Jangho Kim; Juntae Lee; Simyung Chang; Nojun Kwak (ICML, 2022)

Domain Generalization with Relaxed Instance Frequency-wise Normalization for Multi-device Acoustic Scene Classification. - Byeonggeun Kim; Seunghan Yang; Jangho Kim; Hyunsin Park; Juntae Lee; Simyung Chang (INTERSPEECH, 2022)

Model Compression via Position-Based Scaled Gradient. - Jangho Kim; KiYoon Yoo; Nojun Kwak (IEEE Access, 2022)

Detection of Word Adversarial Examples in Text Classification: Benchmark and Baseline via Robust Density Estimation. - KiYoon Yoo; Jangho Kim; Jiho Jang; Nojun Kwak (CoRR, 2022)

QTI Submission to DCASE 2021: residual normalization for device-imbalanced acoustic scene classification with efficient design. - Byeonggeun Kim; Seunghan Yang; Jangho Kim; Simyung Chang (CoRR, 2022)

Finding Efficient Pruned Network via Refined Gradients for Pruned Weights. - Jangho Kim; Jayeon Yoo; Yeji Song; KiYoon Yoo; Nojun Kwak (ACM Multimedia, 2023)

Self-Distilled Self-supervised Representation Learning. - Jiho Jang; Seonhoon Kim; KiYoon Yoo; Chaerin Kong; Jangho Kim; Nojun Kwak (WACV, 2023)

Quantization Robust Pruning With Knowledge Distillation. - Jangho Kim (IEEE Access, 2023)

Cooperative Meta-Learning with Gradient Augmentation. - Jongyun Shin; Seungjin Han; Jangho Kim (UAI, 2024)

SIMULATeQCD: A simple multi-GPU lattice code for QCD calculations. - Lukas Mazur; Dennis Bollweg; Daniel D. A. Clarke; Luis Altenkort; Olaf Kaczmarek; Rasmus Larsen 003; Hai-Tao Shu; Jishnu Goswami; Philipp Scior; Hauke Sandmeyer; Marius Neumann; Henrik Dick; et al. (Comput. Phys. Commun., 2024)

ILP-based resource optimization realized by quantum annealing for optical wide-area communication networks - A framework for solving combinatorial problems of a real-world application by quantum annealing. - Arthur Witt; Jangho Kim; Christopher Körber; Thomas Luu (Frontiers Comput. Sci., 2024)

Sparse Structure Exploration and Re-optimization for Vision Transformer. - Sangho An; Jinwoo Kim; Keonho Lee; Jingang Huh; Chanwoong Kwak; Yujin Lee; Moonsub Jin; Jangho Kim (UAI, 2025)

Quantization-Aware Training With Dynamic and Static Pruning. - Sangho An; Jongyun Shin; Jangho Kim (IEEE Access, 2025)

Magnitude Attention-based Dynamic Pruning. - Jihye Back; Namhyuk Ahn; Jangho Kim (Expert Syst. Appl., 2025)

Layerwise-priority-based gradient adjustment for few-shot learning. - Jangho Kim; Junhoo Lee; Donghoon Han; Nojun Kwak (Expert Syst. Appl., 2025)

Entropy-Guided Meta-Initialization regularization for few-shot text classification. - Jongyun Shin; Jinwoo Kim; Jangho Kim (Knowl. Based Syst., 2025)