• Junhong Kim, Hyungseok Kim, Pilsung Kang.* (2019) Draw A Deep Pattern - Temporal Convolution Neural Network Based Novelty Detection For Smartphone User Authentication From Drawing Patterns. INFORMS 2019 Annual Meeting, Seattle, WA, Oct. 20-23.
  • Seungwan Seo, Donghwa Kim, Pilsung Kang.* (2019) Intrusion Detection Based On Sequential Information Preserving Log Embedding Methods And Anomaly Detection Algorithms. INFORMS 2019 Annual Meeting, Seattle, WA, Oct. 20-23.
  • Heejeong Choi, Pilsung Kang.* (2019) Real-time Significant Wave Height Classification From Raw Ocean Images Based On Convolutional Neural Network. INFORMS 2019 Annual Meeting, Seattle, WA, Oct. 20-23.
  • Myeongjun Jang, Pilsung Kang.* (2018) Sentence Embedding Module Satisfying a Characteristic of Human Language Recognition. INFORMS 2018 Annual Meeting, Phoenix, AZ, Nov. 4-7.
  • Seungwan Seo, Deokseong Seo, Myungjun Jang, Jaeyun Jung, Philsung Kang* (2018) Identifying and visualizing uncommon customer response on machine learning. INFORMS 2018 Annual Meeting, Phoenix, AZ, Nov. 4-7.
  • Donghwa Kim, Deokseong Seo, Suhyoun Cho, Pilsung Kang.* (2017) Multi-co-training for Document Classification using Multi-views. INFORMS 2017 Annual Meeting, Houston, TX, Oct. 22-25.
  • Czang Yeob Kim, Pilsung Kang.* (2017) Aspect Extraction and Polarity Classification of Reviews Based on Deep Neural Network. INFORMS 2017 Annual Meeting, Houston, TX, Oct. 22-25.
  • Hyungseok Kim, Boseop Kim, and Pilsung Kang.* (2016) Evaluating information quality for news articles based on topic modeling. INFORMS 2016 Annual Meeting, Nashville, TN, Nov. 13-16.
  • Junhong Kim, Haedong Kim, Boseop Kim, and Pilsung Kang.* (2016) Strengthening free-text keystroke dynamics based user authentication based on user-adaptive feature construction for one-class classification. INFORMS 2016 Annual Meeting, Nashville, TN, Nov. 13-16.
  • Pilsung Kang, Kyungil Kim, and Nam-Wook Cho. (2013). Toll Fraud Detection of VoIP Services via an Ensemble of Novelty Detection Algorithms, The 17th International Conference on Industrial Engineering Theory, Applications and Practice, Busan, Republic of Korea, Oct. 6-9.
  • Pilsung Kang, Sanggook Kim, Hyunwoo Park, and Hakyeon Lee. (2013). Pre-launch new product demand forecasting based on the Bass diffusion model and an ensemble of regression algorithms, The 2nd International Symposium on System Informatics and Engineering (ISSIE2013), Xian, China.
  • Hyun-joong Kim, Sungzoon Cho, and Pilsung Kang. (2013). Improving word segmentation with unlabeled data, The 2nd International Symposium on System Informatics and Engineering (ISSIE2013), Xian, China.
  • Minhoe Hur, Sungzoon Cho, and Pilsung Kang. (2013). A hierarchical Bayesian model to predict Box-office audience of motion pictures, The 2nd International Symposium on System Informatics and Engineering (ISSIE2013), Xian, China.
  • Taegu Kim, Jungsik Hong, and Pilsung Kang. (2013). Forecasting the Box-Office of motion pictures using social network service data with an ensemble of machine learning algorithm, The International Symposium on Forecasting (ISF 2013), Seoul, Republic of Korea. (Student Travel Granted)
  • Pilsung Kang and Sungzoon Cho. (2011). Keystroke dynamics-based user verification – Who is typing now? INFORMS Annual Meeting (INFORMS 2011), Charolette, NC, USA.
  • Gulanbaier Tuerhong, Pilsung Kang, Sungzoon Cho, Seoung Bum Kim (2011). Integration of novelty score algorithm and control chart technique. INFORMS Annual Meeting (INFORMS 2011), Charolette, NC, USA.
  • Pilsung Kang and Sungzoon Cho. (2009). K-Means clustering seeds initialization based on centrality, sparsity, and isotropy. The 13th International Conferenceon Intelligent Data Engineering and Automated Learning (IDEAL 2009), Burgos, Spain. E. Corchado and H. Yin (Eds.), Lecture Notes in Computer Science LNCS 5788, 109-117.
  • Pilsung Kang and Sungzoon Cho. (2008). Novelty detection based on distance and topological relation. INFORMS Annual Meeting (INFORMS 2008), Washington D.C., USA.
  • Pilsung Kang and Sungzoon Cho. (2007). Customer data reconstruction methods for response modeling. INFORMS Annual Meeting (INFORMS 2007), Seattle, W.A., USA.
  • Pilsung Kang, Seongseob Hwang, and Sungzoon Cho. (2007). Continual retraining of keystroke dynamics based authenticator. The 2nd International Conference on Biometrics (ICB 2007), Seoul, Korea. S.-W. Lee and S.Z. Li (Eds.),Lecture Notes in Computer Science LNCS 4642, 1203-1211.
  • Pilsung Kang and Sungzoon Cho. (2006). EUS SVMSs: Ensemble of under-sampled SVMs for data imbalance problems. The 13th International Conference on Neural Information Processing (ICONIP 2006), Hong Kong, China. I. King, J. Wang, L. Chan, and D. Wang (Eds.), Lecture Notes in Computer Science LNCS 4232, 837-846.
  • Pilsung Kang, Sunghoon Park, Sungzoon Cho, Seong-seob Hwang, and Hyoung-joo Lee. (2006). The effectiveness of artificial rhythms and cues in keystroke dynamics based user authentication. Workshop on Intelligence and Security Informatics (WISI 2006), Singapore. H. Chen, F.Y. Wang, C.C. Yang, D. Zeng, M. Chau, and K. Chang (Eds.), Lecture Notes in Computer Science LNCS 3917, 161-162.

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School of Industrial Management Engineering
College of Engineering, Korea University

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