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ORCIDKee Siong Ng
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- affiliation: Australian National University, Acton, USA
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2020 – today
- 2024
[c19]Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter:
Dynamic Knowledge Injection for AIXI Agents. AAAI 2024: 16388-16397- [i18]Samuel Yang-Zhao, Kee Siong Ng:
Privacy Preserving Reinforcement Learning for Population Processes. CoRR abs/2406.17649 (2024) - [i17]Yang Li, Thilina Ranbaduge, Kee Siong Ng:
Privacy Technologies for Financial Intelligence. CoRR abs/2408.09935 (2024) - 2023
- [j8]Yang Li
, Michael Purcell, Thierry Rakotoarivelo, David Smith, Thilina Ranbaduge, Kee Siong Ng:
Private Graph Data Release: A Survey. ACM Comput. Surv. 55(11): 226:1-226:39 (2023) - [c18]Michael Purcell, Yang Li, Kee Siong Ng:
Split, count, and share: a differentially private set intersection cardinality estimation protocol. UAI 2023: 1684-1694 - [i16]Tianyu Wang, Kee Siong Ng, Miaomiao Liu:
Variational Inference for Scalable 3D Object-centric Learning. CoRR abs/2309.14010 (2023) - [i15]Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter:
Dynamic Knowledge Injection for AIXI Agents. CoRR abs/2312.16184 (2023) - 2022
- [c17]Tianyu Wang, Miaomiao Liu, Kee Siong Ng:
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition. ECCV (23) 2022: 120-135 - [c16]Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng:
A Direct Approximation of AIXI Using Logical State Abstractions. NeurIPS 2022 - [i14]Dawei Chen, Samuel Yang-Zhao, John W. Lloyd, Kee Siong Ng:
Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces. CoRR abs/2206.02178 (2022) - [i13]Yang Li, Kee Siong Ng, Michael Purcell:
A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption. CoRR abs/2208.08125 (2022) - [i12]Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng:
A Direct Approximation of AIXI Using Logical State Abstractions. CoRR abs/2210.06917 (2022) - 2021
- [i11]Sirintra Vaiwsri, Thilina Ranbaduge, Peter Christen, Kee Siong Ng:
Accurate and Efficient Suffix Tree Based Privacy-Preserving String Matching. CoRR abs/2104.03018 (2021) - [i10]Tianyu Wang, Miaomiao Liu, Kee Siong Ng:
Spatially Invariant Unsupervised 3D Object Segmentation with Graph Neural Networks. CoRR abs/2106.05607 (2021) - [i9]Yang Li, Michael Purcell, Thierry Rakotoarivelo, David B. Smith, Thilina Ranbaduge, Kee Siong Ng:
Private Graph Data Release: A Survey. CoRR abs/2107.04245 (2021) - 2020
- [j7]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): 2524-2541 (2020) - [c15]Lingjuan Lyu, Yee Wei Law, Kee Siong Ng, Shibei Xue, Jun Zhao, Mengmeng Yang, Lei Liu:
Towards Distributed Privacy-Preserving Prediction. SMC 2020: 4179-4184
2010 – 2019
- 2019
- [c14]Tom Hamer, Kerry Taylor, Kee Siong Ng, Alwen Tiu:
Private Digital Identity on Blockchain. BlockSW/CKG@ISWC 2019 - [i8]Lingjuan Lyu, Yee Wei Law, Kee Siong Ng:
Distributed Privacy-Preserving Prediction. CoRR abs/1910.11478 (2019) - 2018
- [c13]Yuhang Zhang, Kee Siong Ng, Tania Churchill, Peter Christen:
Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. CIKM 2018: 2213-2221 - 2017
- [c12]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: 107-122 - [i7]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 abs/1708.01402 (2017) - [i6]Yuhang Zhang, Kee Siong Ng, Michael Walker, Pauline Chou, Tania Churchill, Peter Christen:
Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases. CoRR abs/1712.09691 (2017) - 2013
- [j6]Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther:
Probabilities on Sentences in an Expressive Logic. J. Appl. Log. 11(4): 386-420 (2013) - [c11]Daniel McNamara, Paul Wong, Peter Christen, Kee Siong Ng:
Predicting High Impact Academic Papers Using Citation Network Features. PAKDD Workshops 2013: 14-25 - 2012
- [j5]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): 1700-1711 (2012) - [c10]Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling:
Context Tree Switching. DCC 2012: 327-336 - [i5]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 abs/1208.4165 (2012) - [i4]Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther:
Probabilities on Sentences in an Expressive Logic. CoRR abs/1209.2620 (2012) - 2011
- [j4]John W. Lloyd, Kee Siong Ng:
Declarative programming for agent applications. Auton. Agents Multi Agent Syst. 23(2): 224-272 (2011) - [j3]Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver:
A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. 40: 95-142 (2011) - [i3]Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling:
Context Tree Switching. CoRR abs/1111.3182 (2011) - 2010
- [c9]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
Reinforcement Learning via AIXI Approximation. AAAI 2010: 605-611 - [c8]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: 613-622 - [i2]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
Reinforcement Learning via AIXI Approximation. CoRR abs/1007.2049 (2010)
2000 – 2009
- 2009
- [j2]Kee Siong Ng, John W. Lloyd:
Probabilistic reasoning in a classical logic. J. Appl. Log. 7(2): 218-238 (2009) - [i1]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
A Monte Carlo AIXI Approximation. CoRR abs/0909.0801 (2009) - 2008
- [j1]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): 159-205 (2008) - 2007
- [c7]John W. Lloyd, Kee Siong Ng:
Reflections on Agent Beliefs. DALT 2007: 122-139 - [c6]John W. Lloyd, Kee Siong Ng:
Probabilistic and Logical Beliefs. LADS 2007: 19-36 - 2006
- [c5]Kee Siong Ng:
(Agnostic) PAC Learning Concepts in Higher-Order Logic. ECML 2006: 711-718 - [c4]John W. Lloyd, Kee Siong Ng:
Learning Modal Theories. ILP 2006: 320-334 - 2005
- [c3]Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee Siong Ng:
Personalisation for user agents. AAMAS 2005: 603-610 - [c2]Kee Siong Ng:
Generalization Behaviour of Alkemic Decision Trees. ILP 2005: 246-263 - [c1]Kee Siong Ng, John W. Lloyd:
Predicate Selection for Structural Decision Trees. ILP 2005: 264-278
Coauthor Index
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