Personalisation for user agents. - Joshua J. Cole; Matt J. Gray; John W. Lloyd; Kee Siong Ng (AAMAS, 2005)

Generalization Behaviour of Alkemic Decision Trees. - Kee Siong Ng (ILP, 2005)

Predicate Selection for Structural Decision Trees. - Kee Siong Ng; John W. Lloyd (ILP, 2005)

(Agnostic) PAC Learning Concepts in Higher-Order Logic. - Kee Siong Ng (ECML, 2006)

Learning Modal Theories. - John W. Lloyd; Kee Siong Ng (ILP, 2006)

Reflections on Agent Beliefs. - John W. Lloyd; Kee Siong Ng (DALT, 2007)

Probabilistic and Logical Beliefs. - John W. Lloyd; Kee Siong Ng (LADS, 2007)

Probabilistic modelling, inference and learning using logical theories. - Kee Siong Ng; John W. Lloyd; William T. B. Uther (Ann. Math. Artif. Intell., 2008)

A Monte Carlo AIXI Approximation - Joel Veness; Kee Siong Ng; Marcus Hutter; David Silver (CoRR, 2009)

Probabilistic reasoning in a classical logic. - Kee Siong Ng; John W. Lloyd (J. Appl. Log., 2009)

Reinforcement Learning via AIXI Approximation. - Joel Veness; Kee Siong Ng; Marcus Hutter; David Silver (AAAI, 2010)

Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia. - Kee Siong Ng; Yin Shan; D. Wayne Murray; Alison Sutinen; B. Schwarz; David Jeacocke; J. Farrugia (ICDM Workshops, 2010)

Declarative programming for agent applications. - John W. Lloyd; Kee Siong Ng (Auton. Agents Multi Agent Syst., 2011)

A Monte-Carlo AIXI Approximation. - Joel Veness; Kee Siong Ng; Marcus Hutter; William T. B. Uther; David Silver (J. Artif. Intell. Res., 2011)

Context Tree Switching. - Joel Veness; Kee Siong Ng; Marcus Hutter; Michael H. Bowling (DCC, 2012)

The MADlib Analytics Library or MAD Skills, the SQL. - Joseph M. Hellerstein; Christopher Ré; Florian Schoppmann; Daisy Zhe Wang; Eugene Fratkin; Aleksander Gorajek; Kee Siong Ng; Caleb Welton; Xixuan Feng; Kun Li; Arun Kumar 001 (Proc. VLDB Endow., 2012)

Predicting High Impact Academic Papers Using Citation Network Features. - Daniel McNamara; Paul Wong; Peter Christen; Kee Siong Ng (PAKDD Workshops, 2013)

Probabilities on Sentences in an Expressive Logic. - Marcus Hutter; John W. Lloyd; Kee Siong Ng; William T. B. Uther (J. Appl. Log., 2013)

Exploiting Redundancy, Recurrency and Parallelism: How to Link Millions of Addresses with Ten Lines of Code in Ten Minutes. - Yuhang Zhang 001; Tania Churchill; Kee Siong Ng (AusDM, 2017)

Exploiting Redundancy, Recurrence and Parallelism: How to Link Millions of Addresses with Ten Lines of Code in Ten Minutes. - Yuhang Zhang 001; Tania Churchill; Kee Siong Ng (CoRR, 2017)

Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. - Yuhang Zhang 001; Kee Siong Ng; Michael Walker; Pauline Chou; Tania Churchill; Peter Christen (CoRR, 2017)

Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. - Yuhang Zhang 001; Kee Siong Ng; Tania Churchill; Peter Christen (CIKM, 2018)

Private Digital Identity on Blockchain. - Tom Hamer; Kerry Taylor; Kee Siong Ng; Alwen Tiu (BlockSW/CKG@ISWC, 2019)

Distributed Privacy-Preserving Prediction. - Lingjuan Lyu; Yee Wei Law; Kee Siong Ng (CoRR, 2019)

Towards Distributed Privacy-Preserving Prediction. - Lingjuan Lyu; Yee Wei Law; Kee Siong Ng; Shibei Xue; Jun Zhao 007; Mengmeng Yang 002; Lei Liu 031 (SMC, 2020)

Towards Fair and Privacy-Preserving Federated Deep Models. - Lingjuan Lyu; Jiangshan Yu; Karthik Nandakumar; Yitong Li 002; Xingjun Ma; Jiong Jin; Han Yu 001; Kee Siong Ng (IEEE Trans. Parallel Distributed Syst., 2020)

Accurate and Efficient Suffix Tree Based Privacy-Preserving String Matching. - Sirintra Vaiwsri; Thilina Ranbaduge; Peter Christen; Kee Siong Ng (CoRR, 2021)

Spatially Invariant Unsupervised 3D Object Segmentation with Graph Neural Networks. - Tianyu Wang; Miaomiao Liu 001; Kee Siong Ng (CoRR, 2021)

Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition. - Tianyu Wang; Miaomiao Liu 001; Kee Siong Ng (ECCV (23), 2022)

A Direct Approximation of AIXI Using Logical State Abstractions. - Samuel Yang-Zhao; Tianyu Wang; Kee Siong Ng (NeurIPS, 2022)

Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces. - Dawei Chen; Samuel Yang-Zhao; John W. Lloyd; Kee Siong Ng (CoRR, 2022)

A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption. - Yang Li 182; Kee Siong Ng; Michael Purcell (CoRR, 2022)

Split, count, and share: a differentially private set intersection cardinality estimation protocol. - Michael Purcell; Yang Li 182; Kee Siong Ng (UAI, 2023)

Variational Inference for Scalable 3D Object-centric Learning. - Tianyu Wang; Kee Siong Ng; Miaomiao Liu 001 (CoRR, 2023)

Private Graph Data Release: A Survey. - Yang Li 182; Michael Purcell; Thierry Rakotoarivelo; David Smith 001; Thilina Ranbaduge; Kee Siong Ng (ACM Comput. Surv., 2023)

Dynamic Knowledge Injection for AIXI Agents. - Samuel Yang-Zhao; Kee Siong Ng; Marcus Hutter (AAAI, 2024)

Privacy Technologies for Financial Intelligence. - Yang Li 182; Thilina Ranbaduge; Kee Siong Ng (CoRR, 2024)

The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis. - Kee Siong Ng; Samuel Yang-Zhao; Timothy Cadogan-Cowper (CoRR, 2024)

Privacy Preserving Reinforcement Learning for Population Processes. - Samuel Yang-Zhao; Kee Siong Ng (Trans. Mach. Learn. Res., 2024)

Enabling Secure and Ephemeral AI Workloads in Data Mesh Environments. - Chinkit Patel; Kee Siong Ng (CoRR, 2025)