Mental Models 4 Life

My Google Scholar page.

Journal Articles

• • Private Graph Data Release: A Survey,
    Y. Li, M. Purcell, T. Rakotoarivelo, D. Smith, T. Ranbaduge, K.S. Ng, ACM Computing Surveys, 55(11), 1-39, 2023

• • A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption,
    Y. Li, M. Purcell, K.S. Ng, arXiv preprint, 2022

• • Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces,
    D. Chen, S. Yang-Zhao, J.W. Lloyd, K.S. Ng, arXiv preprint, 2022

• • Towards Fair and Privacy-Preserving Federated Deep Models,
    L. Lyu et al, IEEE Transactions on Parallel and Distributed Systems, 31(11), 2524-2541, 2020

• • The MADlib Analytics Library or MAD Skills, the SQL,
    J.M. Hellerstein, C. Re, F. Schoppmann, Z.D. Wang, E. Fratkin, A. Gorajek, K.S. Ng, C. Welton, et al, PVLDB 5(12), pp.1700-1711, 2012.

• • Probabilities on Sentences in an Expressive Logic,
    M. Hutter, J.W. Lloyd, K.S. Ng, W.T.B. Uther, Journal of Applied Logic, vol 11(4), pp. 386-420, 2013. (CoRR abs/1209.2620)

• • A Monte Carlo AIXI Approximation,
    J. Veness, K.S. Ng, M. Hutter, W. Uther, D. Silver, Journal of Artificial Intelligence Research, vol 40, pp. 95-142, 2011. (2014 JAIR-IJCAI Best Paper Prize: Honourable Mention)

• • Declarative Programming for Agent Applications,
    J.W. Lloyd, K.S. Ng, Journal of Autonomous Agents and Multi-Agent Systems, vol 23(2), pp. 224-272, 2011.

• • Probabilistic Reasoning in a Classical Logic,
    K.S. Ng, J.W. Lloyd, Journal of Applied Logic, vol 7(2), pp. 218-238, 2009.

• • Probabilistic Modelling, Inference and Learning using Logical Theories,
    K.S. Ng, J.W. Lloyd, W. Uther, Annals of Mathematics and Artificial Intelligence, vol 54(1), pp. 159-205, 2008.

Selected Conference Papers

• • A Direct Approximation of AIXI using Logical State Abstractions,
    S. Yang-Zhao, T. Wang, K.S. Ng, NeurIPS, 2022

• • Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases,
    Yuhang Zhang, K.S. Ng, Tania Churchill, Peter Christen, In CIKM, 2018

• • Exploiting Redundancy, Recurrence and Parallelism: How to Link Millions of Addresses with Ten Lines of Code in Ten Minutes,
    Yuhang Zhang, Tania Churchill, K.S. Ng, In AusDM, 2017

• • Predicting High Impact Academic Papers using Citation Network Features,
    D. McNamara, P. Wong, P. Christen, K.S. Ng, In DMApps, 2013

• • Unifying Probability and Logic for Learning,
    M. Hutter, J.W. Lloyd, K.S. Ng, W.T.B. Uther, In WL4AI, 2013

• • Context Tree Switching,
    J. Veness, K.S. Ng, M. Hutter, M. Bowling, In IEEE Data Compression Conference, 2012

• • Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia,
    K.S. Ng, Y. Shan, D.W. Murray, A. Sutinen, B. Schwarz, D. Jeacocke, J. Farrugia, In DMAGI, ICDM Workshops 2010, pp. 612-622, 2010

• • Reinforcement Learning via AIXI Approximation,
    J. Veness, K.S. Ng, M. Hutter, D. Silver, In Proceedings of AAAI, pp. 605-611, 2010

• • Learning Modal Theories,
    J.W. Lloyd, K.S. Ng, In Proceedings of ILP 2006, LNAI 4455, pp. 320-334, 2007

• • Agnostic PAC Learning Concepts in Higher-order Logic,
    K.S. Ng, In Proceedings of ECML 2006, LNAI 4212, pp. 711-718, 2006

• • Generalization Bounds for Structural Decision Trees,
    K.S. Ng, In Proceedings of ILP 2005, LNAI 3625, pp. 264-278, 2005

• • Personalisation for User Agents,
    J. Cole, M. Gray, J.W. Lloyd, K.S. Ng, In Proceedings of AAMAS 2005, pp. 603-610, 2005

Theses

• Learning Comprehensible Theories from Structured Data, PhD Thesis, The Australian National University, 2005.

Technical Reports

• A Simple Explanation of Partial Least Squares, K.S. Ng, 2013
• Approximate Inference in Structured Bayesian Networks, R. Kumar, K.S. Ng, 2009
• Agnostic PAC Decision Lists is Hard, K.S. Ng, 2005