L. Chan

发表

Extended Kalman FilterBased Pruning Method for Recurrent Neural Networks

J. Sum, L. Chan, C. Leung, 1998, Neural Computation.

An adaptive training algorithm for back propagation networks

Frank Fallside, Lai-Wan Chan, F. Fallside, 1987 .

The interpolation property of fuzzy polynomial approximation

L. Chan, 1994, Proceedings of ICSIPNN '94. International Conference on Speech, Image Processing and Neural Networks.

Yet another algorithm which can generate topography map

Andrew Chi-Sing Leung, John Sum, Lai-Wan Chan, 1997, IEEE Trans. Neural Networks.

Bidirectional Reinforcement Learning for Asset Allocation

L. Chan, 2022 .

Financial Time Series Prediction Using Non-fixed and Asymmetrical Margin Setting with Momentum in Support Vector Regression

L. Chan, Irwin King, Haiqin Yang, 2004 .

Efficient factor GARCH models and factor-DCC models

Kun Zhang, L. Chan, Kun Zhang, 2009 .

Minimal Nonlinear Distortion Principle for Nonlinear Independent Component Analysis

Lai-Wan Chan, Kun Zhang, L. Chan, 2008 .

SELECTION OF INDEPENDENT FACTOR MODEL IN FINANCE

Lai-Wan Chan, L. Chan, S. Cha, 2001 .

Several Aspects of Pruning Methods inRecursive Least Square Algorithms for

A. Tsoi, L. Chan, N. Leung, 1997 .

Blind Separation of Sources with Dependent Frequency Sub-Components

L. Chan, Kun Zhang, 2006 .

Connection Reduction of the Recurrent Networks

L. Chan, 1995 .

RECENT ADVANCES IN CANTONESE SPEECH RECOGNITIONAlfred

L. Chan, P. Ching, Tan Lee, 2007 .

Neural Information Processing, 13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part II

DeLiang Wang, Lai-Wan Chan, Irwin King, 2006, ICONIP.

Extended Kalman Filter-Based Pruning Method for Recurrent Neural Networks

Andrew Chi-Sing Leung, John Sum, Gilbert H. Young, 1998, Neural Comput..

An Adaptive Method for Subband Decomposition ICA

Lai-Wan Chan, Kun Zhang, L. Chan, 2006, Neural Computation.

Transmission of vector quantized data over a noisy channel

Andrew Chi-Sing Leung, Lai-Wan Chan, L. Chan, 1997, IEEE Trans. Neural Networks.

Nonlinear independent component analysis with minimal nonlinear distortion

Lai-Wan Chan, Kun Zhang, L. Chan, 2007, ICML '07.

Extracting error productions from a neural network-based LR parser

Lai-Wan Chan, Edward Kei Shiu Ho, L. Chan, 2002, Neurocomputing.

Analyzing Holistic Parsers: Implications for Robust Parsing and Systematicity

Lai-Wan Chan, Edward Kei Shiu Ho, L. Chan, 2001, Neural Computation.

How to Design a Connectionist Holistic Parser

Lai-Wan Chan, Edward Kei Shiu Ho, L. Chan, 1999, Neural Computation.

Confluent Preorder Parser as Finite State Automata

Lai-Wan Chan, Edward Kei Shiu Ho, L. Chan, 1996, ICANN.

A Kernel Embedding–Based Approach for Nonstationary Causal Model Inference

Zhitang Chen, Lai-Wan Chan, Shoubo Hu, 2018, Neural Computation.

Causal discovery with scale-mixture model for spatiotemporal variance dependencies

Zhitang Chen, Lai-Wan Chan, Kun Zhang, 2012, NIPS.

Causal Discovery for Linear Non-Gaussian Acyclic Models in the Presence of Latent Gaussian Confounders

Zhitang Chen, Lai-Wan Chan, L. Chan, 2012, LVA/ICA.

Convolutive blind source separation by efficient blind deconvolution and minimal filter distortion

Lai-Wan Chan, Kun Zhang, L. Chan, 2010, Neurocomputing.

Separating Convolutive Mixtures By Pairwise Mutual Information Minimization

Lai-Wan Chan, Kun Zhang, L. Chan, 2007, IEEE Signal Processing Letters.

Dimension reduction as a deflation method in ICA

Lai-Wan Chan, Kun Zhang, L. Chan, 2006, IEEE Signal Process. Lett..

Extended Gaussianization Method for Blind Separation of Post-Nonlinear Mixtures

Lai-Wan Chan, Kun Zhang, L. Chan, 2005, Neural Computation.

To apply score function difference based ICA algorithms to high-dimensional data

Lai-Wan Chan, Kun Zhang, L. Chan, 2005, ESANN.

Dimension Reduction Based on Orthogonality - A Decorrelation Method in ICA

Lai-Wan Chan, Kun Zhang, L. Chan, 2003, ICANN.

Applying Independent Component Analysis to Factor Model in Finance

Lai-Wan Chan, Siu-Ming Cha, L. Chan, 2000, IDEAL.

Discovering Biclusters by Iteratively Sorting with Weighted Correlation Coefficient in Gene Expression Data

Li Teng, Lai-Wan Chan, L. Chan, 2008, J. Signal Process. Syst..

Learning bayesian networks from Markov random fields: An efficient algorithm for linear models

Lai-Wan Chan, Zhenxing Wang, L. Chan, 2012, TKDD.

Learning Causal Relations in Multivariate Time Series Data

Lai-Wan Chan, Zhenxing Wang, L. Chan, 2012, TIST.

Using Bayesian Network Learning Algorithm to Discover Causal Relations in Multivariate Time Series

Lai-Wan Chan, Zhenxing Wang, L. Chan, 2011, 2011 IEEE 11th International Conference on Data Mining.

An efficient causal discovery algorithm for linear models

Lai-Wan Chan, Zhenxing Wang, L. Chan, 2010, KDD.

A Heuristic Partial-Correlation-Based Algorithm for Causal Relationship Discovery on Continuous Data

Lai-Wan Chan, Zhenxing Wang, L. Chan, 2009, IDEAL.

Design of trellis coded vector quantizers using Kohonen maps

L. Chan, A. Leung, 1999, Neural Networks.

Practical method for blind inversion of Wiener systems

Lai-Wan Chan, L. Chan, Kull Zhang, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

Domain Generalization via Multidomain Discriminant Analysis

Zhitang Chen, Lai-Wan Chan, Kun Zhang, 2019, UAI.

Clustered Dynamic Conditional Correlation Multivariate GARCH Model

Lai-Wan Chan, Tu Zhou, L. Chan, 2008, DaWaK.

Transformation of back-propagation networks in multiresolution learning

Lai-Wan Chan, Wing-Chung Chan, L. Chan, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Model-free inference of diffusion networks using RKHS embeddings

L. Chan, Zhitang Chen, Yanhui Geng, 2019, Data Mining and Knowledge Discovery.

Extensions of ICA for Causality Discovery in the Hong Kong Stock Market

Lai-Wan Chan, Kun Zhang, L. Chan, 2006, ICONIP.

ForeNet : fourier recurrent networks for time series prediction

Yingqian Zhang, Lai-Wan Chan, L. Chan, 2000 .

The Minimum Error Minimax Probability Machine

Lai-Wan Chan, Michael R. Lyu, Kaizhu Huang, 2004, J. Mach. Learn. Res..

Extended Kalman filter in recurrent neural network training and pruning

John Sum, Lai-Wan Chan, Cyril S. K. Leung, 1996 .

Support Vector Machine Regression for Volatile Stock Market Prediction

Lai-Wan Chan, Irwin King, Haiqin Yang, 2002, IDEAL.

An Adaptive Bayesian Pruning for Neural Networks in a Non-Stationary Environment

Andrew Chi-Sing Leung, John Sum, Lai-Wan Chan, 1999, Neural Computation.

Proceedings of the 13th international conference on Neural information processing - Volume Part III

DeLiang Wang, Lai-Wan Chan, Irwin King, 2006 .

Independent Factor Reinforcement Learning for Portfolio Management

Lai-Wan Chan, Jian Li, Kun Zhang, 2007, IDEAL.

Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents

Kwong-Sak Leung, Lai-Wan Chan, Helen Meng, 2002, Lecture Notes in Computer Science.

Mining Order Preserving Patterns in Microarray Data by Finding Frequent Orders

Li Teng, Lai-Wan Chan, L. Chan, 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

Order Preserving Clustering by Finding Frequent Orders in Gene Expression Data

Li Teng, Lai-Wan Chan, L. Chan, 2007, PRIB.

Causal Inference and Mechanism Clustering of a Mixture of Additive Noise Models

Zhitang Chen, Lai-Wan Chan, Yanhui Geng, 2018, NeurIPS.

Outliers Treatment in Support Vector Regression for Financial Time Series Prediction

Lai-Wan Chan, Michael R. Lyu, Kaizhu Huang, 2004, ICONIP.

Analysis for a class of winner-take-all model

Andrew Chi-Sing Leung, John Sum, Lai-Wan Chan, 1999, IEEE Trans. Neural Networks.

Intra-block algorithm for digital watermarking

Lai-Wan Chan, Lei Xu, Irwin King, 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

Causal Discovery via Reproducing Kernel Hilbert Space Embeddings

Bernhard Schölkopf, Zhitang Chen, Lai-Wan Chan, 2014, Neural Computation.

Biclustering Gene Expression Profiles by Alternately Sorting with Weighted Correlated Coefficient

Lai-Wan Chan, Li Teng, L. Chan, 2006, 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing.

Reward Adjustment Reinforcement Learning for Risk-averse Asset Allocation

Lai-Wan Chan, Jian Li, L. Chan, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents

Kwong-Sak Leung, Lai-Wan Chan, Helen Meng, 2000 .

Recent Advances In Cantonese Speech Recognition

Lai-Wan Chan, Tan Lee, A. Ng, 1996 .

A pruning method for the recursive least squared algorithm

Kwok-Wo Wong, Andrew Chi-Sing Leung, John Sum, 2001, Neural Networks.

On-line training and pruning for recursive least square algorithms

Lai-Wan Chan, Chi-Sing Leung, Kwok Wo Wong, 1996 .

Bridging Information Criteria and Parameter Shrinkage for Model Selection pdf

Lai-Wan Chan, Aapo Hyvärinen, Kun Zhang, 2013, ArXiv.

The prediction performance of independent factor models

Lai-Wan Chan, L. Chan, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents

L. Chan, K. Leung, Helen M. Meng, 2002, Lecture Notes in Computer Science.

Causal Inference on Multidimensional Data Using Free Probability Theory

Lai-Wan Chan, Furui Liu, L. Chan, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Kernel-Based Nonlinear Independent Component Analysis

Lai-Wan Chan, Kun Zhang, L. Chan, 2007, ICA.

An Algorithm for Trading and Portfolio Management Using Q-learning and Sharpe Ratio Maximization

Lai-Wan Chan, Xiu Xiao Gao, L. Chan, 2000 .

Automatic recognition of continuous Cantonese speech with very large vocabulary

Lai-Wan Chan, Pak-Chung Ching, Alfred Ying Pang Ng, 1997, EUROSPEECH.

Weight groupings in the training of recurrent networks

Lai-Wan Chan, Chi-Cheong Szeto, L. Chan, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Training recurrent network with block-diagonal approximated Levenberg-Marquardt algorithm

Lai-Wan Chan, Chi-Cheong Szeto, L. Chan, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Confluent Preorder Parsing of Deterministic Grammars

Lai-Wan Chan, Edward Kei Shiu Ho, L. Chan, 1997, Connect. Sci..

Causal Inference on Discrete Data via Estimating Distance Correlations

Lai-Wan Chan, Furui Liu, L. Chan, 2016, Neural Computation.