(Google Scholar)

Ph.D. Thesis

• Structure Learning in Markov Logic Networks
  Stanley Kok.
  University of Washington, June 2010.

Journal Papers

• Interpretable Predictive Models for Healthcare via Rational Multi-Layer Perceptrons.
  Thiti Suttaket and Stanley Kok.
  ACM Transactions on Management Information Systems, Volume 15, Issue 3, Sep 2024.
  [code]
  
• Referent Graph Embedding Model for Name Entity Recognition of Chinese Car Reviews.
  Zhao Fang, Qiang Zhang, Stanley Kok, Ling Li, Anning Wang, and Shanlin Yang.
  Knowledge-Based Systems, Volume 233, Dec 2021.
  
• E-Commerce Product Categorization via Machine Translation.
  Liling Tan, Maggie Li Yundi, and Stanley Kok.
  ACM Transactions on Management Information Systems, Volume 11, Issue 3, July 2020.
  [html] [blog]
  
• Combining Levodopa and Virtual Reality-Based Therapy for the Rehabilitation of Upper Limb After Acute Stroke: Pilot Study Part II.
  Geoffrey S. Samuel, Nicodemus E. Oey, Min Choo, Han Ju, Wai Yin Chan, Stanley Kok, Yu Ge, Antonius M Van Dongen, and Yee Sien Ng.
  Singapore Medical Journal, 2017.
  
• CrowdOp: Query Optimization for Declarative Crowdsourcing Systems.
  Ju Fan, Meihui Zhang, Stanley Kok, Meiyu Lu, and Beng Chin Ooi.
  IEEE Transactions on Knowledge and Data Engineering Issue 99, 2015.
  
• The Use of Virtual Reality Based Therapy to Augment Post-Stroke Upper Limb Recovery.
  Geoffrey S. Samuel, Min Choo, Wai Yin Chan, Stanley Kok, Yee Sien Ng.
  Singapore Medical Journal, 2015.
  

Book Chapters

• Markov Logic: A Language and Algorithms for Link Mining.
  Pedro Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, and Parag Singla.
  Link Mining: Models, Algorithms and Applications, edited by P. Yu, C. Faloutsos, and J. Han, Springer, 2010.
• Markov Logic.
  Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson, and Parag Singla.
  Probabilistic Inductive Logic Programming (pp. 92-117), edited by L. De Raedt, P. Frasconi, K. Kersting, and S. Muggleton, Springer, 2008.
• Just Add Weights: Markov Logic for the Semantic Web.
  Pedro Domingos, Daniel Lowd, Stanley Kok , Hoifung Poon, Matthew Richardson, and Parag Singla.
  Uncertain Reasoning for the Semantic Web I (pp. 1-25), edited by P. C. G. Costa, C. d'Amato, N. Fanizzi, K. B. Laskey, K. J. Laskey, T. Lukasiewicz, M. Nickles, and M. Pool, Springer, 2008.

Conference Papers

• Investigating the Effects of Cognitive Biases in Prompts on Large Language Model Outputs. (In print.)
  Yan Sun and Stanley Kok.
  International Conference on Information Systems, 2024. Bangkok, Thailand.
  
• ScamGPT-J: Inside the Scammer's Mind, A Generative AI-based Approach Toward Combating Messaging Scams. (In print.)
  Xue Wen Tan, Kenneth See, and Stanley Kok.
  International Conference on Information Systems, 2024. Bangkok, Thailand.
  
• Prediction of Bank Credit Ratings using Heterogeneous Topological Graph Neural Networks. (In print.)
  Junyi Liu and Stanley Kok.
  Workshop on Information Technologies and Systems, 2024. Bangkok, Thailand.
  
• Explainable Risk Classification in Financial Reports.
  Xue Wen Tan and Stanley Kok.
  International Conference on Information Systems, 2023. Hyderabad, India.
  [video]
• AQE: Argument Quadruplet Extraction via a Quad-Tagging Augmented Generative Approach.
  Jia Guo, Liying Cheng, Wenxuan Zhang, Stanley Kok, Xin Li and Lidong Bing.
  The Findings of the 61st Annual Meeting of the Association for Computational Linguistics, 2023. Toronto, Canada.
  [code]
• Towards Integration of Discriminability and Robustness for Document-Level Relation Extraction.
  Jia Guo, Stanley Kok and Lidong Bing.
  The 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023. Dubrovnik, Croatia.
  [code] [poster] [video]
• In-Training Multicalibrated Survival Analysis For Healthcare via Constrained Optimization.
  Thiti Suttaket and Stanley Kok.
  International Conference on Information Systems, 2022. Copenhagen, Denmark.
  [video]
• Interpretable Predictive Models for Healthcare via Rational Logistic Regression. (Nominated for Best Student Paper Award.)
  Thiti Suttaket, L Vivek Harsha Vardhan, and Stanley Kok.
  International Conference on Information Systems, 2021. Austin, Texas, USA.
  [video]
• BiQUE: Biquaternionic Embeddings of Knowledge Graphs.
  Jia Guo and Stanley Kok.
  Conference on Empirical Methods in Natural Language Processing, 2021. Punta Cana, Dominican Republic.
  [code] [poster] [video]
• Don't Classify, Translate: Multi-Level E-Commerce Product Categorization via Machine Translation
  Maggie Yundi Li, Stanley Kok, and Liling Tan.
  Workshop on Information Technologies and Systems, 2018.
• Efficient Representation Learning for High-Dimensional Imbalance Data.
  Bilal Mirza, Zhiping Lin, Stanley Kok, Xiaoping Lai, Jiuwen Cao, and Jose Sepulveda
  IEEE International Conference on Digital Signal Processing, 2016.
• Multi-Layer Online Sequential Extreme Learning Machine for Image Classification.
  Bilal Mirza, Stanley Kok, and Fei Dong
  Proceedings of the Sixth International Conference on Extreme Learning Machines, 2015. China.
  
• Language Modeling with Sum-Product Networks.
  Wei-Chen Cheng, Stanley Kok, Hoai Vu Pham, Hai Leong Chieu, and Kian Ming A. Chai.
  Proceedings of the Fifteenth Annual Conference of the International Speech Communication Association (INTERSPEECH), 2014. Singapore.
  [code]
• Collective Graph Identification.
  Galileo Namata, Stanley Kok, and Lise Getoor.
  Proceedings of the Seventeenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2011. San Diego, CA.
  
• Learning Markov Logic Networks Using Structural Motifs.
  Stanley Kok and Pedro Domingos.
  Proceedings of the Twenty-Seventh International Conference on Machine Learning, 2010. Haifa, Israel: Omnipress.
  [online appendix] [code] [slides] [poster]
• Hitting the Right Paraphrases in Good Time. (nominated best paper)
  Stanley Kok and Chris Brockett.
  Proceedings of the Eleventh Conference of the North American Chapter of the Association for Computational Linguistics (pp. 145-153), 2010. Los Angeles, California: ACL.
  [slides]
• Extracting Product Information from Email Receipts using Markov Logic.
  Stanley Kok and Wen-tau Yih.
  Proceedings of the Sixth Conference on Email and Anti-Spam, 2009. Mountain View, California.
• Learning Markov Logic Network Structure via Hypergraph Lifting.
  Stanley Kok and Pedro Domingos.
  Proceedings of the Twenty-Sixth International Conference on Machine Learning (pp. 505-512), 2009. Montreal, Canada: Omnipress.
  [online appendix] [code] [slides]
• Extracting Semantic Networks from Text via Relational Clustering.
  Stanley Kok and Pedro Domingos.
  Proceedings of the Nineteenth European Conference on Machine Learning (pp. 624-639), 2008. Antwerp, Belgium: Springer.
  [online appendix] [code] [slides] [poster] [video]
• Statistical Predicate Invention.
  Stanley Kok and Pedro Domingos.
  Proceedings of the Twenty-Fourth International Conference on Machine Learning (pp. 433-440), 2007. Corvallis, Oregon: ACM Press.
  [online appendix] [slides] [video]
• Unifying Logical and Statistical AI.
  Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson, and Parag Singla.
  Proceedings of the Twenty-First National Conference on Artificial Intelligence (pp. 2-7), 2006. Boston, MA: AAAI Press.
• Learning the Structure of Markov Logic Networks.
  Stanley Kok and Pedro Domingos.
  Proceedings of the Twenty-Second International Conference on Machine Learning (pp. 441-448), 2005. Bonn, Germany: ACM Press.
  [online appendix] [slides]
• Web-scale Information Extraction in KnowItAll (Preliminary Results).
  Oren Etzioni, Michael Cafarella, Doug Downey, Stanley Kok, Ana-Maria Popescu, Tal Shaked, Stephen Soderland, Daniel Weld, and Alexander Yates.
  Proceedings of the Thirteenth International Conference on the World Wide Web (pp. 100-109), 2004. New York, New York: ACM Press.

Workshop Papers

• Synthetic Tabular Data Generation with Oblivious Variational Autoencoders: Alleviating the Paucity of Personal Tabular Data for Open Research.
  L Vivek Harsha Vardhan and Stanley Kok.
  ICML Workshop on Healthcare Systems, Population Health, and the Role of Health-Tech, 2020.
• Generating Privacy-Preserving Synthetic Tabular Data Using Oblivious Variational Autoencoders.
  L Vivek Harsha Vardhan and Stanley Kok.
  ICML Workshop on Economics of Privacy and Data Labor, 2020.
• Probabilistic Logic Graph Attention Networks for Reasoning.
  L Vivek Harsha Vardhan, Jia Guo, and Stanley Kok.
  Deep Learning for Graphs Workshop (DL4G@WWW), 2020. Taipei, Taiwan.
  [code]
• Unconstrained Product Categorization with Sequence-to-Sequence Models.
  Maggie Yundi Li, Liling Tan, Stanley Kok, and Ewa Szymanska.
  SIGIR E-Commerce Data Challenge, 2018. Michigan, USA. (6th place out of 28 participants)
• Extracting New Facts and Relations in Knowledge Bases using Matrix Tri-Factorization.
  Tanmoy Mukherjee, Vinay Pande, and Stanley Kok.
  ICML 2013 Workshop on Structured Learning: Inferring Graphs from Structured and Unstructured Inputs. Atlanta, GA.
• Integration of TV News Stories using Markov Logic.
  Stanley Kok.
  AAAI Spring Symposium 2013: Weakly Supervised Learning from Multimedia. Palo Alto, CA.
• Decision-Driven Models with Probabilistic Soft Logic.
  Stephen H. Bach, Matthias Broecheler, Stanley Kok, and Lise Getoor.
  Neural Information Processing (NIPS) Workshop on Predictive Models in Personalized Medicine, 2010. Vancouver, Canada.
• Using Structural Motifs for Learning Markov Logic Networks.
  Stanley Kok and Pedro Domingos.
  Proceedings of the AAAI-10 Workshop on Statistical Relational AI, 2010. Atlanta, Georgia.
• Hypergraph Lifting for Structure Learning in Markov Logic Networks.
  Stanley Kok and Pedro Domingos.
  Proceedings of the International Workshop on Statistical Relational Learning, 2009. Leuven, Belgium.
• Toward Statistical Predicate Invention. (position paper)
  Stanley Kok and Pedro Domingos.
  Proceedings of the ICML-2006 Workshop on Open Problems in Statistical Relational Learning, 2006. Pittsburgh, PA: IMLS.
  [poster]

Technical Reports

• The Alchemy System for Statistical Relational AI (Technical Report).
  Stanley Kok, Marc Sumner, Matthew Richardson, Parag Singla, Hoifung Poon, and Pedro Domingos.
  Department of Computer Science and Engineering, University of Washington, Seattle, WA. 2006-2011. http://alchemy.cs.washington.edu.