James T. Kwok

Orcid: 0000-0002-4828-8248

Affiliations:
  • Hong Kong University of Science and Technology


According to our database1, James T. Kwok authored at least 268 papers between 1993 and 2024.

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Bibliography

2024
A Survey on Time-Series Pre-Trained Models.
IEEE Trans. Knowl. Data Eng., December, 2024

Searching to Exploit Memorization Effect in Deep Learning With Noisy Labels.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Automated Dominative Subspace Mining for Efficient Neural Architecture Search.
IEEE Trans. Circuits Syst. Video Technol., October, 2024

Response Generation in Social Network With Topic and Emotion Constraints.
IEEE Trans. Comput. Soc. Syst., October, 2024

Power Law in Deep Neural Networks: Sparse Network Generation and Continual Learning With Preferential Attachment.
IEEE Trans. Neural Networks Learn. Syst., July, 2024

Illumination Controllable Dehazing Network based on Unsupervised Retinex Embedding.
IEEE Trans. Multim., 2024

Constructing Diverse Inlier Consistency for Partial Point Cloud Registration.
IEEE Trans. Image Process., 2024

CFVNet: An End-to-End Cancelable Finger Vein Network for Recognition.
IEEE Trans. Inf. Forensics Secur., 2024

RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models.
CoRR, 2024

Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation.
CoRR, 2024

Unrevealed Threats: A Comprehensive Study of the Adversarial Robustness of Underwater Image Enhancement Models.
CoRR, 2024

Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning.
CoRR, 2024

Mixup Augmentation with Multiple Interpolations.
CoRR, 2024

Direct Alignment of Language Models via Quality-Aware Self-Refinement.
CoRR, 2024

Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment.
CoRR, 2024

Rendering Graphs for Graph Reasoning in Multimodal Large Language Models.
CoRR, 2024

Improving Sharpness-Aware Minimization by Lookahead.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Efficient Pareto Manifold Learning with Low-Rank Structure.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Multi-Resolution Diffusion Models for Time Series Forecasting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Implicit Concept Removal of Diffusion Models.
Proceedings of the Computer Vision - ECCV 2024, 2024

Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy.
Proceedings of the Computer Vision - ECCV 2024, 2024

Eyes Closed, Safety on: Protecting Multimodal LLMs via Image-to-Text Transformation.
Proceedings of the Computer Vision - ECCV 2024, 2024

Forward-Backward Reasoning in Large Language Models for Mathematical Verification.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Feedback Pyramid Attention Networks for Single Image Super-Resolution.
IEEE Trans. Circuits Syst. Video Technol., September, 2023

Searching a High Performance Feature Extractor for Text Recognition Network.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

AlignVE: Visual Entailment Recognition Based on Alignment Relations.
IEEE Trans. Multim., 2023

Learning the Relation Between Similarity Loss and Clustering Loss in Self-Supervised Learning.
IEEE Trans. Image Process., 2023

Bilinear Scoring Function Search for Knowledge Graph Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning.
CoRR, 2023

Aggregation Weighting of Federated Learning via Generalization Bound Estimation.
CoRR, 2023

Geom-Erasing: Geometry-Driven Removal of Implicit Concept in Diffusion Models.
CoRR, 2023

Effective and Parameter-Efficient Reusing Fine-Tuned Models.
CoRR, 2023

PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.
CoRR, 2023

Domain-Guided Conditional Diffusion Model for Unsupervised Domain Adaptation.
CoRR, 2023

Forward-Backward Reasoning in Large Language Models for Verification.
CoRR, 2023

No Place to Hide: Dual Deep Interaction Channel Network for Fake News Detection based on Data Augmentation.
CoRR, 2023

Adversarial Attack and Defense for Dehazing Networks.
CoRR, 2023

Nonparametric Teaching for Multiple Learners.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Hyper-parameter Optimization with Cubic Regularization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Nonparametric Iterative Machine Teaching.
Proceedings of the International Conference on Machine Learning, 2023

Non-autoregressive Conditional Diffusion Models for Time Series Prediction.
Proceedings of the International Conference on Machine Learning, 2023

Effective Structured Prompting by Meta-Learning and Representative Verbalizer.
Proceedings of the International Conference on Machine Learning, 2023

Enhancing Meta Learning via Multi-Objective Soft Improvement Functions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Adaptive Policy to Employ Sharpness-Aware Minimization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Cross-Modal Matching and Adaptive Graph Attention Network for RGB-D Scene Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2023

KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Leveraging per Image-Token Consistency for Vision-Language Pre-training.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Positive-Unlabeled Node Classification with Structure-aware Graph Learning.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Efficient Low-Rank Semidefinite Programming With Robust Loss Functions.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization.
J. Mach. Learn. Res., 2022

New transformation method in continuous particle swarm optimisation for feature selection.
Int. J. Wirel. Mob. Comput., 2022

Pyramidal dense attention networks for single image super-resolution.
IET Image Process., 2022

Efficient Variance Reduction for Meta-learning.
Proceedings of the International Conference on Machine Learning, 2022

Subspace Learning for Effective Meta-Learning.
Proceedings of the International Conference on Machine Learning, 2022

Revisiting Over-smoothing in BERT from the Perspective of Graph.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Query Rewriting in TaoBao Search.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Noniterative Sparse LS-SVM Based on Globally Representative Point Selection.
IEEE Trans. Neural Networks Learn. Syst., 2021

Learning to Hash With Dimension Analysis Based Quantizer for Image Retrieval.
IEEE Trans. Multim., 2021

Side Information Fusion for Recommender Systems over Heterogeneous Information Network.
ACM Trans. Knowl. Discov. Data, 2021

Generalizing from a Few Examples: A Survey on Few-shot Learning.
ACM Comput. Surv., 2021

Pyramidal Dense Attention Networks for Lightweight Image Super-Resolution.
CoRR, 2021

Tensorizing Subgraph Search in the Supernet.
CoRR, 2021

A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Learning.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Dropout's Dream Land: Generalization from Learned Simulators to Reality.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Effective Meta-Regularization by Kernelized Proximal Regularization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SEEN: Few-Shot Classification with SElf-ENsemble.
Proceedings of the International Joint Conference on Neural Networks, 2021

SparseBERT: Rethinking the Importance Analysis in Self-attention.
Proceedings of the 38th International Conference on Machine Learning, 2021

Time Series Anomaly Detection with Multiresolution Ensemble Decoding.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction.
Proceedings of the Federated Learning - Privacy and Incentive, 2020

Generalized Convolutional Sparse Coding With Unknown Noise.
IEEE Trans. Image Process., 2020

A Survey of Label-noise Representation Learning: Past, Present and Future.
CoRR, 2020

Efficient Low-Rank Matrix Learning by Factorizable Nonconvex Regularization.
CoRR, 2020

Efficient Neural Interaction Function Search for Collaborative Filtering.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Searching to Exploit Memorization Effect in Learning with Noisy Labels.
Proceedings of the 37th International Conference on Machine Learning, 2020

Effective Decoding in Graph Auto-Encoder Using Triadic Closure.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Low-Rank Matrix Learning Using Biconvex Surrogate Minimization.
IEEE Trans. Neural Networks Learn. Syst., 2019

Accelerated and Inexact Soft-Impute for Large-Scale Matrix and Tensor Completion.
IEEE Trans. Knowl. Data Eng., 2019

Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Multi-objective Neural Architecture Search via Predictive Network Performance Optimization.
CoRR, 2019

Searching for Interaction Functions in Collaborative Filtering.
CoRR, 2019

Blockwise Adaptivity: Faster Training and Better Generalization in Deep Learning.
CoRR, 2019

General Convolutional Sparse Coding with Unknown Noise.
CoRR, 2019

Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Normalization Helps Training of Quantized LSTM.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Dynamic Unit Surgery for Deep Neural Network Compression and Acceleration.
Proceedings of the International Joint Conference on Neural Networks, 2019

Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations.
Proceedings of the 36th International Conference on Machine Learning, 2019

Analysis of Quantized Models.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Fast-Solving Quasi-Optimal LS-S<sup>3</sup>VM Based on an Extended Candidate Set.
IEEE Trans. Neural Networks Learn. Syst., 2018

Multi-Label Learning with Global and Local Label Correlation.
IEEE Trans. Knowl. Data Eng., 2018

Scalable Online Convolutional Sparse Coding.
IEEE Trans. Image Process., 2018

Corrigendum to "Multi-label learning in the independent label sub-spaces" [Pattern Recognition Letters 97(2017) 8-12].
Pattern Recognit. Lett., 2018

Power Law in Sparsified Deep Neural Networks.
CoRR, 2018

Learning with Heterogeneous Side Information Fusion for Recommender Systems.
CoRR, 2018

Scalable Robust Matrix Factorization with Nonconvex Loss.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Convolutional Sparse Coding with Sample-Dependent Dictionary.
Proceedings of the 35th International Conference on Machine Learning, 2018

Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data.
Proceedings of the 35th International Conference on Machine Learning, 2018

Loss-aware Weight Quantization of Deep Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
A Note on the Unification of Adaptive Online Learning.
IEEE Trans. Neural Networks Learn. Syst., 2017

Multi-Label learning in the independent label sub-spaces.
Pattern Recognit. Lett., 2017

Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
J. Mach. Learn. Res., 2017

Online Convolutional Sparse Coding.
CoRR, 2017

Zero-shot learning with a partial set of observed attributes.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Follow the Moving Leader in Deep Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Loss-aware Binarization of Deep Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

Collaborative Filtering with Social Local Models.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Special issue: First International Conference on Big Data and Smart Computing (BigComp2014).
Data Knowl. Eng., 2016

Fast Learning with Nonconvex L1-2 Regularization.
CoRR, 2016

Learning of Generalized Low-Rank Models: A Greedy Approach.
CoRR, 2016

Aggregating Crowdsourced Ordinal Labels via Bayesian Clustering.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Greedy Learning of Generalized Low-Rank Models.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Fast-and-Light Stochastic ADMM.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Asynchronous Distributed Semi-Stochastic Gradient Optimization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Towards Safe Semi-Supervised Learning for Multivariate Performance Measures.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Efficient Learning of Timeseries Shapelets.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Fast Nonsmooth Regularized Risk Minimization with Continuation.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Machine Learning.
Proceedings of the Springer Handbook of Computational Intelligence, 2015

Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines.
IEEE Trans. Neural Networks Learn. Syst., 2015

Large-Scale Nyström Kernel Matrix Approximation Using Randomized SVD.
IEEE Trans. Neural Networks Learn. Syst., 2015

Scalable Nonparametric Low-Rank Kernel Learning Using Block Coordinate Descent.
IEEE Trans. Neural Networks Learn. Syst., 2015

Bayes-Optimal Hierarchical Multilabel Classification.
IEEE Trans. Knowl. Data Eng., 2015

Fast Distributed Asynchronous SGD with Variance Reduction.
CoRR, 2015

Fast Second Order Stochastic Backpropagation for Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Collaborative filtering via co-factorization of individuals and groups.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Accelerated Inexact Soft-Impute for Fast Large-Scale Matrix Completion.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Fast Low-Rank Matrix Learning with Nonconvex Regularization.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Colorization by Patch-Based Local Low-Rank Matrix Completion.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification.
IEEE Trans. Neural Networks Learn. Syst., 2014

Simple randomized algorithms for online learning with kernels.
Neural Networks, 2014

Selected papers from the 2011 International Conference on Neural Information Processing (ICONIP 2011).
Neurocomputing, 2014

Learning to Predict from Crowdsourced Data.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Fast Stochastic Alternating Direction Method of Multipliers.
Proceedings of the 31th International Conference on Machine Learning, 2014

Asynchronous Distributed ADMM for Consensus Optimization.
Proceedings of the 31th International Conference on Machine Learning, 2014

Accelerated Stochastic Gradient Method for Composite Regularization.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Gradient Descent with Proximal Average for Nonconvex and Composite Regularization.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Accurate Integration of Aerosol Predictions by Smoothing on a Manifold.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Multilabel Classification with Label Correlations and Missing Labels.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Convex and scalable weakly labeled SVMs.
J. Mach. Learn. Res., 2013

Accurate Probability Calibration for Multiple Classifiers.
Proceedings of the IJCAI 2013, 2013

Efficient Kernel Learning from Side Information Using ADMM.
Proceedings of the IJCAI 2013, 2013

Flexible Nonparametric Kernel Learning with Different Loss Functions.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels.
Proceedings of the 30th International Conference on Machine Learning, 2013

Efficient Multi-label Classification with Many Labels.
Proceedings of the 30th International Conference on Machine Learning, 2013

Efficient Learning for Models with DAG-Structured Parameter Constraints.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Learning from High-Dimensional Data in Multitask/Multilabel Classification.
Proceedings of the 2nd IAPR Asian Conference on Pattern Recognition, 2013

2012
Efficient Sparse Modeling With Automatic Feature Grouping.
IEEE Trans. Neural Networks Learn. Syst., 2012

Bilinear Probabilistic Principal Component Analysis.
IEEE Trans. Neural Networks Learn. Syst., 2012

A brief introduction to the special issue for ISNN2010.
Neurocomputing, 2012

Convex Multitask Learning with Flexible Task Clusters.
Proceedings of the 29th International Conference on Machine Learning, 2012

Hierarchical Multilabel Classification with Minimum Bayes Risk.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2011
A Hybrid PSO-BFGS Strategy for Global Optimization of Multimodal Functions.
IEEE Trans. Syst. Man Cybern. Part B, 2011

Domain Adaptation via Transfer Component Analysis.
IEEE Trans. Neural Networks, 2011

Incorporating cellular sorting structure for better prediction of protein subcellular locations.
J. Exp. Theor. Artif. Intell., 2011

Structured clustering with automatic kernel adaptation.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

MultiLabel Classification on Tree- and DAG-Structured Hierarchies.
Proceedings of the 28th International Conference on Machine Learning, 2011

Time and space efficient spectral clustering via column sampling.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Incorporating the loss function into discriminative clustering of structured outputs.
IEEE Trans. Neural Networks, 2010

Clustered Nyström method for large scale manifold learning and dimension reduction.
IEEE Trans. Neural Networks, 2010

Simplifying mixture models through function approximation.
IEEE Trans. Neural Networks, 2010

Fast and accurate kernel density approximation using a divide-and-conquer approach.
J. Zhejiang Univ. Sci. C, 2010

Text detection in images using sparse representation with discriminative dictionaries.
Image Vis. Comput., 2010

Spectral and Semidefinite Relaxation of the CLUHSIC Algorithm.
Proceedings of the SIAM International Conference on Data Mining, 2010

Manifold regularization for structured outputs via the joint kernel.
Proceedings of the International Joint Conference on Neural Networks, 2010

Making Large-Scale Nyström Approximation Possible.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Online multiple instance learning with no regret.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Cost-Sensitive Semi-Supervised Support Vector Machine.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Maximum Margin Clustering Made Practical.
IEEE Trans. Neural Networks, 2009

Building Sparse Multiple-Kernel SVM Classifiers.
IEEE Trans. Neural Networks, 2009

Maximum Penalized Likelihood Kernel Regression for Fast Adaptation.
IEEE Trans. Speech Audio Process., 2009

Density-Weighted Nyström Method for Computing Large Kernel Eigensystems.
Neural Comput., 2009

Tighter and Convex Maximum Margin Clustering.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Multiple Kernel Clustering.
Proceedings of the SIAM International Conference on Data Mining, 2009

A Convex Method for Locating Regions of Interest with Multi-instance Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Accelerated Gradient Methods for Stochastic Optimization and Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Prototype vector machine for large scale semi-supervised learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Semi-supervised learning using label mean.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Maximum Margin Clustering with Multivariate Loss Function.
Proceedings of the ICDM 2009, 2009

Accelerated Gradient Method for Multi-task Sparse Learning Problem.
Proceedings of the ICDM 2009, 2009

Unsupervised Maximum Margin Feature Selection with manifold regularization.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008
Matrix-Variate Factor Analysis and Its Applications.
IEEE Trans. Neural Networks, 2008

Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines.
IEEE Trans. Neural Networks, 2008

Improved Nyström low-rank approximation and error analysis.
Proceedings of the Machine Learning, 2008

Transferring Localization Models across Space.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

Transfer Learning via Dimensionality Reduction.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
A Class of Single-Class Minimax Probability Machines for Novelty Detection.
IEEE Trans. Neural Networks, 2007

Face recognition using spectral features.
Pattern Recognit., 2007

SVDD-Based Pattern Denoising.
Neural Comput., 2007

Surrogate maximization/minimization algorithms and extensions.
Mach. Learn., 2007

End-to-end privacy control in service outsourcing of human intensive processes: A multi-layered Web service integration approach.
Inf. Syst. Frontiers, 2007

Ensembles of Partially Trained SVMs with Multiplicative Updates.
Proceedings of the IJCAI 2007, 2007

Marginalized Multi-Instance Kernels.
Proceedings of the IJCAI 2007, 2007

Simpler core vector machines with enclosing balls.
Proceedings of the Machine Learning, 2007

Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
A novel incremental principal component analysis and its application for face recognition.
IEEE Trans. Syst. Man Cybern. Part B, 2006

Generalized Core Vector Machines.
IEEE Trans. Neural Networks, 2006

Efficient hyperkernel learning using second-order cone programming.
IEEE Trans. Neural Networks, 2006

Multidimensional Vector Regression for Accurate and Low-Cost Location Estimation in Pervasive Computing.
IEEE Trans. Knowl. Data Eng., 2006

Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting.
IEEE Trans. Speech Audio Process., 2006

Model-based transductive learning of the kernel matrix.
Mach. Learn., 2006

Large-Scale Sparsified Manifold Regularization.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Efficient kernel feature extraction for massive data sets.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Learning the Kernel in Mahalanobis One-Class Support Vector Machines.
Proceedings of the International Joint Conference on Neural Networks, 2006

Wavelet-Based Feature Extraction for Microarray Data Classification.
Proceedings of the International Joint Conference on Neural Networks, 2006

Efficient Classification of Multi-label and Imbalanced Data using Min-Max Modular Classifiers.
Proceedings of the International Joint Conference on Neural Networks, 2006

Multimodal Registration using the Discrete Wavelet Frame Transform.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Gene Feature Extraction Using T-Test Statistics and Kernel Partial Least Squares.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Block-quantized kernel matrix for fast spectral embedding.
Proceedings of the Machine Learning, 2006

Locally adaptive classification piloted by uncertainty.
Proceedings of the Machine Learning, 2006

A regularization framework for multiple-instance learning.
Proceedings of the Machine Learning, 2006

Facial Image Reconstruction by SVDD-Based Pattern De-noising.
Proceedings of the Advances in Biometrics, International Conference, 2006

Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Diversified SVM Ensembles for Large Data Sets.
Proceedings of the Machine Learning: ECML 2006, 2006

Accelerated Convergence Using Dynamic Mean Shift.
Proceedings of the Computer Vision, 2006

2005
Kernel Eigenvoice Speaker Adaptation.
IEEE Trans. Speech Audio Process., 2005

Core Vector Machines: Fast SVM Training on Very Large Data Sets.
J. Mach. Learn. Res., 2005

Accurate and Low-cost Location Estimation Using Kernels.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Core Vector Regression for very large regression problems.
Proceedings of the Machine Learning, 2005

Position estimation for wireless sensor networks.
Proceedings of the Global Telecommunications Conference, 2005. GLOBECOM '05, St. Louis, Missouri, USA, 28 November, 2005

Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

Very Large SVM Training using Core Vector Machines.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

Towards end-to-end privacy control in the outsourcing of marketing activities: a web service integration solution.
Proceedings of the 7th International Conference on Electronic Commerce, 2005

2004
Fusing images with different focuses using support vector machines.
IEEE Trans. Neural Networks, 2004

The pre-image problem in kernel methods.
IEEE Trans. Neural Networks, 2004

Dissimilarity learning for nominal data.
Pattern Recognit., 2004

Speedup of kernel eigenvoice speaker adaptation by embedded kernel PCA.
Proceedings of the 8th International Conference on Spoken Language Processing, 2004

Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm.
Proceedings of the Machine Learning, 2004

Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model.
Proceedings of the Machine Learning, 2004

A study of various composite kernels for kernel eigenvoice speaker adaptation.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Incremental PCA based face recognition.
Proceedings of the 8th International Conference on Control, 2004

Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo.
Proceedings of the Nineteenth National Conference on Artificial Intelligence, 2004

2003
Linear dependency between ε and the input noise in ε-support vector regression.
IEEE Trans. Neural Networks, 2003

Texture classification using the support vector machines.
Pattern Recognit., 2003

Mining customer product ratings for personalized marketing.
Decis. Support Syst., 2003

Eigenvoice Speaker Adaptation via Composite Kernel PCA.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Parametric Distance Metric Learning with Label Information.
Proceedings of the IJCAI-03, 2003

Learning with Idealized Kernels.
Proceedings of the Machine Learning, 2003

2002
Multifocus image fusion using artificial neural networks.
Pattern Recognit. Lett., 2002

Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images.
Inf. Fusion, 2002

Improving De-Noising by Coefficient De-Noising and Dyadic Wavelet Transform.
Proceedings of the 16th International Conference on Pattern Recognition, 2002

Fusing Images with Multiple Focuses Using Support Vector Machines.
Proceedings of the Artificial Neural Networks, 2002

2001
Combination of images with diverse focuses using the spatial frequency.
Inf. Fusion, 2001

Linear Dependency between epsilon and the Input Noise in epsilon-Support Vector Regression.
Proceedings of the Artificial Neural Networks, 2001

Applying the Bayesian Evidence Framework to \nu -Support Vector Regression.
Proceedings of the Machine Learning: EMCL 2001, 2001

Bayesian Support Vector Regression.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
The evidence framework applied to support vector machines.
IEEE Trans. Neural Networks Learn. Syst., 2000

Rival Penalized Competitive Learning for Model-Based Sequence Clustering.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

1999
Moderating the outputs of support vector machine classifiers.
IEEE Trans. Neural Networks, 1999

Integrating the evidence framework and the support vector machine.
Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

1998
Support vector mixture for classification and regression problems.
Proceedings of the Fourteenth International Conference on Pattern Recognition, 1998

Automated Text Categorization Using Support Vector Machine.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

1997
Objective functions for training new hidden units in constructive neural networks.
IEEE Trans. Neural Networks, 1997

Constructive algorithms for structure learning in feedforward neural networks for regression problems.
IEEE Trans. Neural Networks, 1997

1996
Use of bias term in projection pursuit learning improves approximation and convergence properties.
IEEE Trans. Neural Networks, 1996

Bayesian Regularization in Constructive Neural Networks.
Proceedings of the Artificial Neural Networks, 1996

1995
Improving the approximation and convergence capabilities of projection pursuit learning.
Neural Process. Lett., 1995

Efficient cross-validation for feedforward neural networks.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

1993
Experimental analysis of input weight freezing in constructive neural networks.
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993


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