Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Kian Hsiang Low

Federated Bayesian Optimization via Thompson Sampling


Oct 22, 2020
Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet

* Accepted to 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Extended version with proofs and additional experimental details and results, 25 pages 

  Access Paper or Ask Questions

R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games


Jun 30, 2020
Zhongxiang Dai, Yizhou Chen, Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho

* Accepted to 37th International Conference on Machine Learning (ICML 2020), Extended version with proofs and additional experimental details and results, 27 pages 

  Access Paper or Ask Questions

Nonmyopic Gaussian Process Optimization with Macro-Actions


Feb 22, 2020
Dmitrii Kharkovskii, Chun Kai Ling, Kian Hsiang Low

* 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020), Extended version with proofs, 32 pages 

  Access Paper or Ask Questions

Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression


Dec 05, 2019
Tong Teng, Jie Chen, Yehong Zhang, Kian Hsiang Low

* 34th AAAI Conference on Artificial Intelligence (AAAI 2020), Extended version with derivations, 12 pages 

  Access Paper or Ask Questions

Inverse Reinforcement Learning with Missing Data


Nov 16, 2019
Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet


  Access Paper or Ask Questions

Implicit Posterior Variational Inference for Deep Gaussian Processes


Oct 26, 2019
Haibin Yu, Yizhou Chen, Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet

* 33rd Annual Conference on Neural Information Processing Systems (NeurIPS-19) 

  Access Paper or Ask Questions

Bayesian Optimization with Binary Auxiliary Information


Jun 17, 2019
Yehong Zhang, Zhongxiang Dai, Kian Hsiang Low

* 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Extended version with derivations and more experimental results, 19 pages 

  Access Paper or Ask Questions

GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection


Mar 15, 2019
Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran, Kian Hsiang Low, Mun Choon Chan

* to appear in 2019 IEEE Conference on Communications and Network Security (CNS) 

  Access Paper or Ask Questions

Towards Robust ResNet: A Small Step but A Giant Leap


Feb 28, 2019
Jingfeng Zhang, Bo Han, Laura Wynter, Kian Hsiang Low, Mohan Kankanhalli


  Access Paper or Ask Questions

Collective Online Learning via Decentralized Gaussian Processes in Massive Multi-Agent Systems


May 23, 2018
Trong Nghia Hoang, Quang Minh Hoang, Kian Hsiang Low, Jonathan How

* Under review for NIPS-18 

  Access Paper or Ask Questions

Decentralized High-Dimensional Bayesian Optimization with Factor Graphs


Jan 24, 2018
Trong Nghia Hoang, Quang Minh Hoang, Ruofei Ouyang, Kian Hsiang Low

* 32nd AAAI Conference on Artificial Intelligence (AAAI 2018), Extended version with proofs, 13 pages 

  Access Paper or Ask Questions

Gaussian Process Decentralized Data Fusion Meets Transfer Learning in Large-Scale Distributed Cooperative Perception


Nov 16, 2017
Ruofei Ouyang, Kian Hsiang Low

* 32nd AAAI Conference on Artificial Intelligence (AAAI 2018), Extended version with proofs, 14 pages 

  Access Paper or Ask Questions

Stochastic Variational Inference for Fully Bayesian Sparse Gaussian Process Regression Models


Nov 01, 2017
Haibin Yu, Trong Nghia Hoang, Kian Hsiang Low, Patrick Jaillet


  Access Paper or Ask Questions

A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression


Nov 18, 2016
Quang Minh Hoang, Trong Nghia Hoang, Kian Hsiang Low

* 31st AAAI Conference on Artificial Intelligence (AAAI 2017), Extended version with proofs, 11 pages 

  Access Paper or Ask Questions

Multi-Agent Continuous Transportation with Online Balanced Partitioning


Jul 28, 2016
Chao Wang, Somchaya Liemhetcharat, Kian Hsiang Low

* 2 pages, published in the proceedings of the 15th AAMAS conference 

  Access Paper or Ask Questions

DrMAD: Distilling Reverse-Mode Automatic Differentiation for Optimizing Hyperparameters of Deep Neural Networks


Apr 06, 2016
Jie Fu, Hongyin Luo, Jiashi Feng, Kian Hsiang Low, Tat-Seng Chua

* International Joint Conference on Artificial Intelligence, IJCAI, 2016 

  Access Paper or Ask Questions

Near-Optimal Active Learning of Multi-Output Gaussian Processes


Nov 24, 2015
Yehong Zhang, Trong Nghia Hoang, Kian Hsiang Low, Mohan Kankanhalli

* 30th AAAI Conference on Artificial Intelligence (AAAI 2016), Extended version with proofs, 13 pages 

  Access Paper or Ask Questions

Gaussian Process Planning with Lipschitz Continuous Reward Functions: Towards Unifying Bayesian Optimization, Active Learning, and Beyond


Nov 21, 2015
Chun Kai Ling, Kian Hsiang Low, Patrick Jaillet

* 30th AAAI Conference on Artificial Intelligence (AAAI 2016), Extended version with proofs, 17 pages 

  Access Paper or Ask Questions

Parallel Gaussian Process Regression for Big Data: Low-Rank Representation Meets Markov Approximation


Nov 17, 2014
Kian Hsiang Low, Jiangbo Yu, Jie Chen, Patrick Jaillet

* 29th AAAI Conference on Artificial Intelligence (AAAI 2015), Extended version with proofs, 10 pages 

  Access Paper or Ask Questions

Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations


Aug 09, 2014
Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan, Patrick Jaillet

* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 

  Access Paper or Ask Questions

Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena


Aug 09, 2014
Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan, Ali Oran, Patrick Jaillet, John Dolan, Gaurav Sukhatme

* Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012) 

  Access Paper or Ask Questions

GP-Localize: Persistent Mobile Robot Localization using Online Sparse Gaussian Process Observation Model


Apr 22, 2014
Nuo Xu, Kian Hsiang Low, Jie Chen, Keng Kiat Lim, Etkin Baris Ozgul

* 28th AAAI Conference on Artificial Intelligence (AAAI 2014), Extended version with proofs, 10 pages 

  Access Paper or Ask Questions

A General Framework for Interacting Bayes-Optimally with Self-Interested Agents using Arbitrary Parametric Model and Model Prior


Mar 16, 2014
Trong Nghia Hoang, Kian Hsiang Low

* 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), Extended version with proofs, 10 pages 

  Access Paper or Ask Questions

Gaussian Process-Based Decentralized Data Fusion and Active Sensing for Mobility-on-Demand System


Jun 02, 2013
Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan

* Robotics: Science and Systems (RSS 2013), Extended version with proofs, 10 pages 

  Access Paper or Ask Questions

Information-Theoretic Approach to Efficient Adaptive Path Planning for Mobile Robotic Environmental Sensing


May 27, 2013
Kian Hsiang Low, John M. Dolan, Pradeep Khosla

* 19th International Conference on Automated Planning and Scheduling (ICAPS 2009), Extended version with proofs, 11 pages 

  Access Paper or Ask Questions

Interactive POMDP Lite: Towards Practical Planning to Predict and Exploit Intentions for Interacting with Self-Interested Agents


Apr 18, 2013
Trong Nghia Hoang, Kian Hsiang Low

* 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), Extended version with proofs, 24 pages 

  Access Paper or Ask Questions

Multi-Robot Informative Path Planning for Active Sensing of Environmental Phenomena: A Tale of Two Algorithms


Feb 05, 2013
Nannan Cao, Kian Hsiang Low, John M. Dolan

* 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), Extended version with proofs, 15 pages 

  Access Paper or Ask Questions