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All publications by James T. Kwok
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Priors for Diversity in Generative Latent Variable Models
James T. Kwok and Ryan P. Adams
Advances in Neural Information Processing Systems 25, 2012


Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification
Wei Bi and James T. Kwok
Advances in Neural Information Processing Systems 25, 2012


Convex Multitask Learning with Flexible Task Clusters
Wenliang Zhong and James T. Kwok
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Efficient Sparse Modeling with Automatic Feature Grouping
Wenliang Zhong and James T. Kwok
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Multi-Label Classification on Tree- and DAG-Structured Hierarchies
Wei Bi and James T. Kwok
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Making Large-Scale Nystr{\"o}m Approximation Possible
Mu Li, James T. Kwok and Bao-liang Lu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Prototype vector machine for large scale semi-supervised learning
Kai Zhang, James T. Kwok and Bahram Parvin
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Semi-supervised learning using label mean
Yu-feng Li, James T. Kwok and Zhi-hua Zhou
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Accelerated Gradient Methods for Stochastic Optimization and Online Learning
Chonghai Hu, Weike Pan and James T. Kwok
Advances in Neural Information Processing Systems 22, 2009


Tighter and Convex Maximum Margin Clustering
Yu-feng Li, Ivor W. Tsang, James T. Kwok and Zhi-hua Zhou
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Improved Nystr{\&}ouml;m low-rank approximation and error analysis
Kai Zhang, Ivor W. Tsang and James T. Kwok
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Maximum margin clustering made practical
Kai Zhang, Ivor W. Tsang and James T. Kwok
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Simpler core vector machines with enclosing balls
Ivor W. Tsang, AndrĂ¡s Kocsor and James T. Kwok
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Block-quantized kernel matrix for fast spectral embedding
Kai Zhang and James T. Kwok
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Locally adaptive classification piloted by uncertainty
Juan Dai, Shuicheng Yan, Xiaoou Tang and James T. Kwok
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


A regularization framework for multiple-instance learning
Pak-ming Cheung and James T. Kwok
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Simplifying Mixture Models through Function Approximation
Kai Zhang and James T. Kwok
Advances in Neural Information Processing Systems 19, 2006


Large-Scale Sparsified Manifold Regularization
Ivor W. Tsang and James T. Kwok
Advances in Neural Information Processing Systems 19, 2006


Core Vector Regression for very large regression problems
Ivor W. Tsang, James T. Kwok and Kimo T. Lai
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Core Vector Machines: Fast SVM Training on Very Large Data Sets
Ivor W. Tsang, James T. Kwok and Pak-ming Cheung
Journal of Machine Learning Research, 2005


Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
Zhihua Zhang, Dit-yan Yeung and James T. Kwok
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Zhihua Zhang, James T. Kwok and Dit-yan Yeung
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


The Pre-Image Problem in Kernel Methods
James T. Kwok and Ivor W. Tsang
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Learning with Idealized Kernels
James T. Kwok and Ivor W. Tsang
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Eigenvoice Speaker Adaptation via Composite Kernel PCA
James T. Kwok, Brian Mak and Simon Ho
Advances in Neural Information Processing Systems 16, 2003