Laiwan Chan

Publication Activity (10 Years)

Years Active: 1998-2019
Publications (10 Years): 12

Top Topics

Learning Bayesian Networks

Reproducing Kernel Hilbert Space

Causal Discovery

Top Venues

ACM Trans. Intell. Syst. Technol.

Publications

Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan
Domain Generalization via Multidomain Discriminant Analysis. CoRR (2019)
Shoubo Hu, Bogdan Cautis, Zhitang Chen, Laiwan Chan, Yanhui Geng, Xiuqiang He
Model-free inference of diffusion networks using RKHS embeddings. Data Min. Knowl. Discov. 33 (2) (2019)
Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan
Domain Generalization via Multidomain Discriminant Analysis. UAI (2019)
Shoubo Hu, Zhitang Chen, Laiwan Chan
A Kernel Embedding-based Approach for Nonstationary Causal Model Inference. CoRR (2018)
Shoubo Hu, Zhitang Chen, Laiwan Chan
A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference. Neural Comput. 30 (5) (2018)
Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Laiwan Chan, Yanhui Geng
Causal Inference and Mechanism Clustering of a Mixture of Additive Noise Models. CoRR (2018)
Furui Liu, Laiwan Chan
Confounder Detection in High Dimensional Linear Models using First Moments of Spectral Measures. CoRR (2018)
Furui Liu, Laiwan Chan
Causal Inference on Discrete Data via Estimating Distance Correlations. CoRR (2018)
Furui Liu, Laiwan Chan
Confounder Detection in High-Dimensional Linear Models Using First Moments of Spectral Measures. Neural Comput. 30 (8) (2018)
Furui Liu, Laiwan Chan
On the Relations of Theoretical Foundations of Different Causal Inference Algorithms. IDEAL (2017)
Furui Liu, Laiwan Chan
Causal Discovery on Discrete Data with Extensions to Mixture Model. ACM Trans. Intell. Syst. Technol. 7 (2) (2016)
Furui Liu, Laiwan Chan
Causal Inference on Discrete Data via Estimating Distance Correlations. Neural Comput. 28 (5) (2016)
Zhitang Chen, Kun Zhang, Laiwan Chan, Bernhard Schölkopf
Causal Discovery via Reproducing Kernel Hilbert Space Embeddings. Neural Comput. 26 (7) (2014)
Zhitang Chen, Kun Zhang, Laiwan Chan
Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method. ICDM (2013)
Zhitang Chen, Laiwan Chan
Causality in Linear Nongaussian Acyclic Models in the Presence of Latent Gaussian Confounders. Neural Comput. 25 (6) (2013)
Kun Zhang, Heng Peng, Laiwan Chan, Aapo Hyvärinen
Bridging Information Criteria and Parameter Shrinkage for Model Selection. CoRR (2013)
Zhitang Chen, Kun Zhang, Laiwan Chan
Causal discovery with scale-mixture model for spatiotemporal variance dependencies. NIPS (2012)
Zhenxing Wang, Laiwan Chan
Learning Causal Relations in Multivariate Time Series Data. ACM Trans. Intell. Syst. Technol. 3 (4) (2012)
Zhenxing Wang, Laiwan Chan
Learning bayesian networks from Markov random fields: An efficient algorithm for linear models. ACM Trans. Knowl. Discov. Data 6 (3) (2012)
Zhitang Chen, Laiwan Chan
Causal Discovery for Linear Non-Gaussian Acyclic Models in the Presence of Latent Gaussian Confounders. LVA/ICA (2012)
Zhenxing Wang, Laiwan Chan
Using Bayesian Network Learning Algorithm to Discover Causal Relations in Multivariate Time Series. ICDM (2011)
Zhitang Chen, Laiwan Chan
New approaches for solving permutation indeterminacy and scaling ambiguity in frequency domain separation of convolved mixtures. IJCNN (2011)
Zhenxing Wang, Laiwan Chan
An efficient causal discovery algorithm for linear models. KDD (2010)
Kun Zhang, Heng Peng, Laiwan Chan, Aapo Hyvärinen
ICA with Sparse Connections: Revisited. ICA (2009)
Zhenxing Wang, Laiwan Chan
A Heuristic Partial-Correlation-Based Algorithm for Causal Relationship Discovery on Continuous Data. IDEAL (2009)
Tu Zhou, Laiwan Chan
Clustered Dynamic Conditional Correlation Multivariate GARCH Model. DaWaK (2008)
Li Teng, Laiwan Chan
Discovering Distinct Patterns in Gene Expression Profiles. J. Integr. Bioinform. 5 (2) (2008)
Li Teng, Laiwan Chan
Discovering Biclusters by Iteratively Sorting with Weighted Correlation Coefficient in Gene Expression Data. J. Signal Process. Syst. 50 (3) (2008)
Li Teng, Laiwan Chan
Order Preserving Clustering by Finding Frequent Orders in Gene Expression Data. PRIB (2007)
Li Teng, Laiwan Chan
Mining Order Preserving Patterns in Microarray Data by Finding Frequent Orders. BIBE (2007)
Kun Zhang, Laiwan Chan
Nonlinear independent component analysis with minimal nonlinear distortion. ICML (2007)
Kun Zhang, Laiwan Chan
Kernel-Based Nonlinear Independent Component Analysis. ICA (2007)
Kun Zhang, Laiwan Chan
Separating Convolutive Mixtures By Pairwise Mutual Information Minimization. IEEE Signal Process. Lett. 14 (12) (2007)
Jian Li, Kun Zhang, Laiwan Chan
Independent Factor Reinforcement Learning for Portfolio Management. IDEAL (2007)
Jian Li, Laiwan Chan
Reward Adjustment Reinforcement Learning for Risk-averse Asset Allocation. IJCNN (2006)
Haiqin Yang, Kaizhu Huang, Laiwan Chan, Irwin King, Michael R. Lyu
Outliers Treatment in Support Vector Regression for Financial Time Series Prediction. ICONIP (2004)
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan
The Minimum Error Minimax Probability Machine. J. Mach. Learn. Res. 5 (2004)
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan
Biased Minimax Probability Machine for Medical Diagnosis. AI&M (2004)
Haiqin Yang, Laiwan Chan, Irwin King
Support Vector Machine Regression for Volatile Stock Market Prediction. IDEAL (2002)
Daqing Chen, Laiwan Chan
An Adaptive Learning Rate for Training Ring-Structured Recurrent Network. ICONIP (1998)
Daqing Chen, Laiwan Chan
Training Recurrent Neural Networks by Using Parallel Recursive Prediction Error Algorithm. ICONIP (1998)