Kee Siong Ng - RankMe

48 papers A* 3A 3B 5Misc 1Journal 29Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Enabling Secure and Ephemeral AI Workloads in Data Mesh Environments. CoRR Chinkit Patel, Kee Siong Ng
2024	A*	`conf`	Dynamic Knowledge Injection for AIXI Agents. AAAI Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
2024	J	`jnl`	Privacy Preserving Reinforcement Learning for Population Processes. CoRR Samuel Yang-Zhao, Kee Siong Ng
2024	J	`jnl`	Privacy Preserving Reinforcement Learning for Population Processes. Trans. Mach. Learn. Res. Samuel Yang-Zhao, Kee Siong Ng
2024	J	`jnl`	Privacy Technologies for Financial Intelligence. CoRR Yang Li, Thilina Ranbaduge, Kee Siong Ng
2024	J	`jnl`	The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis. CoRR Kee Siong Ng, Samuel Yang-Zhao, Timothy Cadogan-Cowper
2023	J	`jnl`	Dynamic Knowledge Injection for AIXI Agents. CoRR Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
2023	J	`jnl`	Private Graph Data Release: A Survey. ACM Comput. Surv. Yang Li, Michael Purcell, Thierry Rakotoarivelo, David Smith, Thilina Ranbaduge, Kee Siong Ng
2023	A	`conf`	Split, count, and share: a differentially private set intersection cardinality estimation protocol. UAI Michael Purcell, Yang Li, Kee Siong Ng
2023	J	`jnl`	Variational Inference for Scalable 3D Object-centric Learning. CoRR Tianyu Wang, Kee Siong Ng, Miaomiao Liu
2022	A*	`conf`	A Direct Approximation of AIXI Using Logical State Abstractions. NeurIPS Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng
2022	J	`jnl`	A Direct Approximation of AIXI Using Logical State Abstractions. CoRR Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng
2022	J	`jnl`	A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption. CoRR Yang Li, Kee Siong Ng, Michael Purcell
2022	J	`jnl`	Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces. CoRR Dawei Chen, Samuel Yang-Zhao, John W. Lloyd, Kee Siong Ng
2022	—	`conf`	Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition. ECCV (23) Tianyu Wang, Miaomiao Liu, Kee Siong Ng
2021	J	`jnl`	Accurate and Efficient Suffix Tree Based Privacy-Preserving String Matching. CoRR Sirintra Vaiwsri, Thilina Ranbaduge, Peter Christen, Kee Siong Ng
2021	J	`jnl`	Private Graph Data Release: A Survey. CoRR Yang Li, Michael Purcell, Thierry Rakotoarivelo, David B. Smith, Thilina Ranbaduge, Kee Siong Ng
2021	J	`jnl`	Spatially Invariant Unsupervised 3D Object Segmentation with Graph Neural Networks. CoRR Tianyu Wang, Miaomiao Liu, Kee Siong Ng
2020	B	`conf`	Towards Distributed Privacy-Preserving Prediction. SMC Lingjuan Lyu, Yee Wei Law, Kee Siong Ng, Shibei Xue, Jun Zhao, Mengmeng Yang, Lei Liu
2020	J	`jnl`	Towards Fair and Privacy-Preserving Federated Deep Models. IEEE Trans. Parallel Distributed Syst. Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng
2019	J	`jnl`	Distributed Privacy-Preserving Prediction. CoRR Lingjuan Lyu, Yee Wei Law, Kee Siong Ng
2019	—	`conf`	Private Digital Identity on Blockchain. BlockSW/CKG@ISWC Tom Hamer, Kerry Taylor, Kee Siong Ng, Alwen Tiu
2018	A	`conf`	Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. CIKM Yuhang Zhang, Kee Siong Ng, Tania Churchill, Peter Christen
2017	J	`jnl`	Exploiting Redundancy, Recurrence and Parallelism: How to Link Millions of Addresses with Ten Lines of Code in Ten Minutes. CoRR Yuhang Zhang, Tania Churchill, Kee Siong Ng
2017	Misc	`conf`	Exploiting Redundancy, Recurrency and Parallelism: How to Link Millions of Addresses with Ten Lines of Code in Ten Minutes. AusDM Yuhang Zhang, Tania Churchill, Kee Siong Ng
2017	J	`jnl`	Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. CoRR Yuhang Zhang, Kee Siong Ng, Michael Walker, Pauline Chou, Tania Churchill, Peter Christen
2013	—	`conf`	Predicting High Impact Academic Papers Using Citation Network Features. PAKDD Workshops Daniel McNamara, Paul Wong, Peter Christen, Kee Siong Ng
2013	J	`jnl`	Probabilities on Sentences in an Expressive Logic. J. Appl. Log. Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther
2012	B	`conf`	Context Tree Switching. DCC Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
2012	J	`jnl`	Probabilities on Sentences in an Expressive Logic CoRR Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther
2012	J	`jnl`	The MADlib Analytics Library or MAD Skills, the SQL CoRR 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
2012	J	`jnl`	The MADlib Analytics Library or MAD Skills, the SQL. Proc. VLDB Endow. 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
2011	J	`jnl`	A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver
2011	J	`jnl`	Context Tree Switching CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
2011	J	`jnl`	Declarative programming for agent applications. Auton. Agents Multi Agent Syst. John W. Lloyd, Kee Siong Ng
2010	—	`conf`	Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia. ICDM Workshops Kee Siong Ng, Yin Shan, D. Wayne Murray, Alison Sutinen, B. Schwarz, David Jeacocke, J. Farrugia
2010	J	`jnl`	Reinforcement Learning via AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2010	A*	`conf`	Reinforcement Learning via AIXI Approximation. AAAI Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2009	J	`jnl`	A Monte Carlo AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2009	J	`jnl`	Probabilistic reasoning in a classical logic. J. Appl. Log. Kee Siong Ng, John W. Lloyd
2008	J	`jnl`	Probabilistic modelling, inference and learning using logical theories. Ann. Math. Artif. Intell. Kee Siong Ng, John W. Lloyd, William T. B. Uther
2007	—	`conf`	Probabilistic and Logical Beliefs. LADS John W. Lloyd, Kee Siong Ng
2007	—	`conf`	Reflections on Agent Beliefs. DALT John W. Lloyd, Kee Siong Ng
2006	—	`conf`	(Agnostic) PAC Learning Concepts in Higher-Order Logic. ECML Kee Siong Ng
2006	B	`conf`	Learning Modal Theories. ILP John W. Lloyd, Kee Siong Ng
2005	B	`conf`	Generalization Behaviour of Alkemic Decision Trees. ILP Kee Siong Ng
2005	A	`conf`	Personalisation for user agents. AAMAS Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee Siong Ng
2005	B	`conf`	Predicate Selection for Structural Decision Trees. ILP Kee Siong Ng, John W. Lloyd