Kee Siong Ng

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 22

Top Topics

Set Intersection

Spatially Invariant

Privacy Preserving

Homomorphic Encryption

Top Venues

BlockSW/CKG@ISWC

Publications

Samuel Yang-Zhao, Kee Siong Ng
Privacy Preserving Reinforcement Learning for Population Processes. CoRR (2024)
Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
Dynamic Knowledge Injection for AIXI Agents. AAAI (2024)
Michael Purcell, Yang Li, Kee Siong Ng
Split, count, and share: a differentially private set intersection cardinality estimation protocol. UAI (2023)
Yang Li, Michael Purcell, Thierry Rakotoarivelo, David Smith, Thilina Ranbaduge, Kee Siong Ng
Private Graph Data Release: A Survey. ACM Comput. Surv. 55 (11) (2023)
Tianyu Wang, Kee Siong Ng, Miaomiao Liu
Variational Inference for Scalable 3D Object-centric Learning. CoRR (2023)
Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
Dynamic Knowledge Injection for AIXI Agents. CoRR (2023)
Yang Li, Kee Siong Ng, Michael Purcell
A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption. CoRR (2022)
Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng
A Direct Approximation of AIXI Using Logical State Abstractions. NeurIPS (2022)
Tianyu Wang, Miaomiao Liu, Kee Siong Ng
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition. ECCV (23) (2022)
Dawei Chen, Samuel Yang-Zhao, John W. Lloyd, Kee Siong Ng
Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces. CoRR (2022)
Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng
A Direct Approximation of AIXI Using Logical State Abstractions. CoRR (2022)
Yang Li, Michael Purcell, Thierry Rakotoarivelo, David B. Smith, Thilina Ranbaduge, Kee Siong Ng
Private Graph Data Release: A Survey. CoRR (2021)
Sirintra Vaiwsri, Thilina Ranbaduge, Peter Christen, Kee Siong Ng
Accurate and Efficient Suffix Tree Based Privacy-Preserving String Matching. CoRR (2021)
Tianyu Wang, Miaomiao Liu, Kee Siong Ng
Spatially Invariant Unsupervised 3D Object Segmentation with Graph Neural Networks. CoRR (2021)
Lingjuan Lyu, Yee Wei Law, Kee Siong Ng, Shibei Xue, Jun Zhao, Mengmeng Yang, Lei Liu
Towards Distributed Privacy-Preserving Prediction. SMC (2020)
Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng
Towards Fair and Privacy-Preserving Federated Deep Models. IEEE Trans. Parallel Distributed Syst. 31 (11) (2020)
Tom Hamer, Kerry Taylor, Kee Siong Ng, Alwen Tiu
Private Digital Identity on Blockchain. BlockSW/CKG@ISWC (2019)
Lingjuan Lyu, Yee Wei Law, Kee Siong Ng
Distributed Privacy-Preserving Prediction. CoRR (2019)
Yuhang Zhang, Kee Siong Ng, Tania Churchill, Peter Christen
Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. CIKM (2018)
Yuhang Zhang, Kee Siong Ng, Michael Walker, Pauline Chou, Tania Churchill, Peter Christen
Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. CoRR (2017)
Yuhang Zhang, Tania Churchill, Kee Siong Ng
Exploiting Redundancy, Recurrence and Parallelism: How to Link Millions of Addresses with Ten Lines of Code in Ten Minutes. CoRR (2017)
Yuhang Zhang, Tania Churchill, Kee Siong Ng
Exploiting Redundancy, Recurrency and Parallelism: How to Link Millions of Addresses with Ten Lines of Code in Ten Minutes. AusDM (2017)
Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther
Probabilities on Sentences in an Expressive Logic. J. Appl. Log. 11 (4) (2013)
Daniel McNamara, Paul Wong, Peter Christen, Kee Siong Ng
Predicting High Impact Academic Papers Using Citation Network Features. PAKDD Workshops (2013)
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
The MADlib Analytics Library or MAD Skills, the SQL CoRR (2012)
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
The MADlib Analytics Library or MAD Skills, the SQL. Proc. VLDB Endow. 5 (12) (2012)
Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
Context Tree Switching. DCC (2012)
Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther
Probabilities on Sentences in an Expressive Logic CoRR (2012)
Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver
A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. 40 (2011)
John W. Lloyd, Kee Siong Ng
Declarative programming for agent applications. Auton. Agents Multi Agent Syst. 23 (2) (2011)
Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
Context Tree Switching CoRR (2011)
Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
Reinforcement Learning via AIXI Approximation. AAAI (2010)
Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
Reinforcement Learning via AIXI Approximation CoRR (2010)
Kee Siong Ng, Yin Shan, D. Wayne Murray, Alison Sutinen, B. Schwarz, David Jeacocke, J. Farrugia
Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia. ICDM Workshops (2010)
Kee Siong Ng, John W. Lloyd
Probabilistic reasoning in a classical logic. J. Appl. Log. 7 (2) (2009)
Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
A Monte Carlo AIXI Approximation CoRR (2009)
Kee Siong Ng, John W. Lloyd, William T. B. Uther
Probabilistic modelling, inference and learning using logical theories. Ann. Math. Artif. Intell. 54 (1-3) (2008)
John W. Lloyd, Kee Siong Ng
Probabilistic and Logical Beliefs. LADS (2007)
John W. Lloyd, Kee Siong Ng
Reflections on Agent Beliefs. DALT (2007)
Kee Siong Ng
(Agnostic) PAC Learning Concepts in Higher-Order Logic. ECML (2006)
John W. Lloyd, Kee Siong Ng
Learning Modal Theories. ILP (2006)
Kee Siong Ng
Generalization Behaviour of Alkemic Decision Trees. ILP (2005)
Kee Siong Ng, John W. Lloyd
Predicate Selection for Structural Decision Trees. ILP (2005)
Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee Siong Ng
Personalisation for user agents. AAMAS (2005)