Kwak, Nojun

A Comprehensive Overhaul of Feature Distillation

Heo, B., Kim, J., Yun, S., Park, H., Kwak, N., & Choi, J. Y. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 706

Paraphrasing Complex Network: Network Compression via Factor Transfer

Kim, J., Park, S., & Kwak, N. (2018) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 411

LSQ+: Improving low-bit quantization through learnable offsets and better initialization

Bhalgat, Y., Lee, J., Nagel, M., Blankevoort, T., & Kwak, N. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 236

Feature Fusion for Online Mutual Knowledge Distillation

Kim, J., Hyun, M., Chung, I., & Kwak, N. (2021) · 2020 25th International Conference on Pattern Recognition (ICPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 106

PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation

Kim, J., Chang, S., & Kwak, N. (2021) · Interspeech 2021

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 85

Interpolation-based Semi-supervised Learning for Object Detection

Jeong, J., Verma, V., Hyun, M., Kannala, J., & Kwak, N. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 66

QKD: Quantization-aware Knowledge Distillation

Kim, J., Bhalgat, Y., Lee, J., Patel, C., & Kwak, N. (2019) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 44

Detection of adversarial examples in text classification: Benchmark and baseline via robust density estimation

Yoo, K., Kim, J., Jang, J., & Kwak, N. (2022) · Findings of the Association for Computational Linguistics: ACL 2022

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 33