Kaizhu Huang

发表

Multi-scale Attention Consistency for Multi-label Image Classification

Haotian Xu, Xiaobo Jin, Qiufeng Wang, 2020, International Conference on Neural Information Processing.

Classifier Ensemble Using a Heuristic Learning with Sparsity and Diversity

Kaizhu Huang, Xu-Cheng Yin, Hongwei Hao, 2012, ICONIP.

Generative adversarial networks with decoder-encoder output noises

Kaizhu Huang, Guoqiang Zhong, Wei Gao, 2020, Neural Networks.

Beyond Attributes: Adversarial Erasing Embedding Network for Zero-shot Learning pdf

Kaizhu Huang, Xiao-Bo Jin, Jianyu Miao, 2018, ArXiv.

W-Net: One-Shot Arbitrary-Style Chinese Character Generation with Deep Neural Networks

Rui Zhang, Kaizhu Huang, Guanyu Yang, 2018, ICONIP.

Guided Policy Search for Sequential Multitask Learning

Hong Qiao, Kaizhu Huang, Amir Hussain, 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Machine Learning: Modeling Data Locally and Globally

Kaizhu Huang, Michael R. Lyu, Irwin King, 2008 .

Survey on data science with population-based algorithms

Bin Liu, Yuhui Shi, Kaizhu Huang, 2016 .

Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach

Mingjie Sun, Yunchao Wei, Kaizhu Huang, 2019, AAAI.

Discriminative training of Bayesian Chow-Liu multinet classifiers

Kaizhu Huang, Michael R. Lyu, Irwin King, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

Automatic Design of Deep Networks with Neural Blocks

Kaizhu Huang, Guoqiang Zhong, Wei Gao, 2019, Cognitive Computation.

Correlation Filter Selection for Visual Tracking Using Reinforcement Learning

Kaizhu Huang, Yao Zhao, Jeyarajan Thiyagalingam, 2018, IEEE Transactions on Circuits and Systems for Video Technology.

Improving Chow-Liu Tree Performance by Mining Association Rules

Kaizhu Huang, Michael R. Lyu, Irwin King, 2004 .

Multi-Task Low-Rank Metric Learning Based on Common Subspace

Kaizhu Huang, Cheng-Lin Liu, Peipei Yang, 2011, ICONIP.

Exchange rate prediction with non-numerical information

Qian Liu, Kaizhu Huang, Xu-Cheng Yin, 2010, Neural Computing and Applications.

An SVM-Based High-accurate Recognition Approach for Handwritten Numerals by Using Difference Features

Jun Sun, Yoshinobu Hotta, Satoshi Naoi, 2007 .

Dimensionality Reduction by Minimal Distance Maximization

Bo Xu, Kaizhu Huang, Cheng-Lin Liu, 2010, 2010 20th International Conference on Pattern Recognition.

A scalable deep neural network architecture for multi-building and multi-floor indoor localization based on Wi-Fi fingerprinting

Sanghyuk Lee, Kaizhu Huang, Kyeong Soo Kim, 2017, ArXiv.

Zero-Shot Learning via Attribute Regression and Class Prototype Rectification

Meng Wang, Zhetao Li, Kaizhu Huang, 2018, IEEE Transactions on Image Processing.

Ranking Entity Based on Both of Word Frequency and Word Sematic Features pdf

Kaizhu Huang, Zhiwei Yan, Xiao-Bo Jin, 2016, ArXiv.

A Novel Discriminative Naive Bayesian Network for Classification

Zenglin Xu, Kaizhu Huang, Zhangbing Zhou, 2007 .

Field Support Vector Machines

Kaizhu Huang, Xu-Yao Zhang, Haochuan Jiang, 2017, IEEE Transactions on Emerging Topics in Computational Intelligence.

Supervised Self-taught Learning: Actively transferring knowledge from unlabeled data

Zenglin Xu, Michael R. Lyu, Kaizhu Huang, 2009, 2009 International Joint Conference on Neural Networks.

A review on multi-task metric learning

Kaizhu Huang, Amir Hussain, Peipei Yang, 2018 .

Beyond Attributes: High-Order Attribute Features for Zero-Shot Learning

Kaizhu Huang, Guo-Sen Xie, Xiao-Bo Jin, 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

Robust generative adversarial network pdf

Kaizhu Huang, Yuan He, Jimin Xiao, 2019, Machine Learning.

Learning Latent Features With Infinite Nonnegative Binary Matrix Trifactorization

Rui Zhang, Kaizhu Huang, Amir Hussain, 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.

Geometry Preserving Multi-task Metric Learning

Kaizhu Huang, Cheng-Lin Liu, Peipei Yang, 2012, ECML/PKDD.

CDMC'19 - The 10th International Cybersecurity Data Mining Competition

Iqbal Gondal, Kitsuchart Pasupa, Shaoning Pang, 2020, ICONIP.

m-SNE: Multiview Stochastic Neighbor Embedding

Kaizhu Huang, Dacheng Tao, Yang Mu, 2011, IEEE Trans. Syst. Man Cybern. Part B.

Unsupervised Dimensionality Reduction for Gaussian Mixture Model

Rui Zhang, Kaizhu Huang, Xi Yang, 2014, ICONIP.

MCRN: A New Content-Based Music Classification and Recommendation Network

Kaizhu Huang, Guoqiang Zhong, Haizhen Wang, 2020, International Conference on Neural Information Processing.

Biased support vector machine for relevance feedback in image retrieval

Kaizhu Huang, I. King, Chu-Hong Hoi, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

SimpleGAN Stabilizing Generative Adversarial Networks with Simple Distributions

Kaizhu Huang, Rui Zhang, Amir Hussain, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

A Novel Hybrid Approach for Combining Deep and Traditional Neural Networks

Kaizhu Huang, Rui Zhang, Shufei Zhang, 2014, ICONIP.

WSDM'15 Workshop Summary / Scalable Data Analytics: Theory and Applications

Michael R. Lyu, Kaizhu Huang, Irwin King, 2015, WSDM.

Compressing Deep Networks by Neuron Agglomerative Clustering

Kaizhu Huang, Guoqiang Zhong, Junyu Dong, 2020, Sensors.

Customer churn prediction in the telecommunication sector using a rough set approach

Kaizhu Huang, Amir Hussain, Adnan Amin, 2017, Neurocomputing.

VSB-DVM: An End-to-End Bayesian Nonparametric Generalization of Deep Variational Mixture Model

Kaizhu Huang, Rui Zhang, Xi Yang, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Style-Neutralized Pattern Classification Based on Adversarially Trained Upgraded U-Net

Kaizhu Huang, Amir Hussain, Haochuan Jiang, 2019, Cognitive Computation.

Text Categorization with Diversity Random Forests

Kaizhu Huang, Chun Yang, Xu-Cheng Yin, 2014, ICONIP.

State Primitive Learning to Overcome Catastrophic Forgetting in Robotics

Hong Qiao, Kaizhu Huang, Zhiyong Liu, 2020, Cognitive Computation.

Generative Adversarial Classifier for Handwriting Characters Super-Resolution

Rui Zhang, Kaizhu Huang, Jimin Xiao, 2020, Pattern Recognit..

Maxi–Min Margin Machine: Learning Large Margin Classifiers Locally and Globally

Michael R. Lyu, Kaizhu Huang, Irwin King, 2008, IEEE Transactions on Neural Networks.

Arbitrary Norm Support Vector Machines

Michael R. Lyu, Kaizhu Huang, Irwin King, 2009, Neural Computation.

Improving Disentanglement-Based Image-to-Image Translation with Feature Joint Block Fusion

Kaizhu Huang, Rui Zhang, Qiu-Feng Wang, 2019, BICS.

Towards Better Forecasting by Fusing Near and Distant Future Visions

Kaizhu Huang, Zibin Zheng, Jiezhu Cheng, 2019, AAAI.

A novel kernel-based maximum a posteriori classification method

Zenglin Xu, Michael R. Lyu, Kaizhu Huang, 2009, Neural Networks.

An Investigation of Machine Learning and Neural Computation Paradigms in the Design of Clinical Decision Support Systems (CDSSs)

Kaizhu Huang, Amir Hussain, Bin Luo, 2016, BICS.

Outliers Treatment in Support Vector Regression for Financial Time Series Prediction

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

Feature Redirection Network for Few-Shot Classification

Kaizhu Huang, Guoqiang Zhong, Yanan Wang, 2020, ICONIP.

Three-Dimensional Local Energy-Based Shape Histogram (3D-LESH): A Novel Feature Extraction Technique

Kaizhu Huang, Amir Hussain, Summrina Kanwal Wajid, 2017, Expert Syst. Appl..

Learning large margin classifiers locally and globally

Michael R. Lyu, Kaizhu Huang, Irwin King, 2004, ICML.

SDRNF: generating scalable and discriminative random nonlinear features from data

Kaizhu Huang, Rui Zhang, Haoda Chu, 2016 .

Residual attention-based multi-scale script identification in scene text images

Kaizhu Huang, Qiu-Feng Wang, Yannis Goulermas, 2021, Neurocomputing.

Sparse Metric Learning via Smooth Optimization

Kaizhu Huang, Colin Campbell, Yiming Ying, 2009, NIPS.

Random Features and Random Neurons for Brain-Inspired Big Data Analytics

Kaizhu Huang, Amir Hussain, Mandar Gogate, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

A Hybrid Handwritten Chinese Address Recognition Approach

Yoshinobu Hotta, Satoshi Naoi, Kaizhu Huang, 2006, ICONIP.

Triple loss for hard face detection

Kaizhu Huang, Stephen Marshall, Zheng Wang, 2020, Neurocomputing.

Banzhaf random forests: Cooperative game theory based random forests with consistency

Kaizhu Huang, Junyu Dong, Guoqiang Zhong, 2018, Neural Networks.

Novel Field-Support Vector Regression-Based Soft Sensor for Accurate Estimation of Solar Irradiance

Kaizhu Huang, Ka Lok Man, Jieming Ma, 2017, IEEE Transactions on Circuits and Systems I: Regular Papers.

Explainable Tensorized Neural Ordinary Differential Equations for Arbitrary-Step Time Series Prediction pdf

Rui Zhang, Kaizhu Huang, Xi Yang, 2020, IEEE Transactions on Knowledge and Data Engineering.

Field Support Vector Machines

Kaizhu Huang, Xu-Yao Zhang, Haochuan Jiang, 2017, IEEE Transactions on Emerging Topics in Computational Intelligence.

Editorial: Collaborative Computing for Data-Driven Systems

Kaizhu Huang, Honghao Gao, Andrei Tchernykh, 2020, Mob. Networks Appl..

A Unified Gradient Regularization Family for Adversarial Examples

Kaizhu Huang, Hai-Ning Liang, Chunchuan Lyu, 2015, 2015 IEEE International Conference on Data Mining.

Graphical lasso quadratic discriminant function and its application to character recognition

Satoshi Naoi, Bo Xu, Kaizhu Huang, 2014, Neurocomputing.

Neural Information Processing

Kaizhu Huang, Kok Wai Wong, Andrew Teoh, 2014, Lecture Notes in Computer Science.

Feature Transformation with Class Conditional Decorrelation

Kaizhu Huang, Cheng-Lin Liu, Xu-Yao Zhang, 2013, 2013 IEEE 13th International Conference on Data Mining.

A Novel Deep Density Model for Unsupervised Learning

Rui Zhang, Xi Yang, Kaizhu Huang, 2018, Cognitive Computation.

Enhanced protein fold recognition through a novel data integration approach

Kaizhu Huang, Colin Campbell, Yiming Ying, 2009, BMC Bioinformatics.

Statistical Entity Ranking with Domain Knowledge

Kaizhu Huang, Zhiwei Yan, Xiao-Bo Jin, 2016, NLPCC/ICCPOL.

Style Neutralization Generative Adversarial Classifier

Rui Zhang, Kaizhu Huang, Amir Hussain, 2018, BICS.

Novel Artificial Immune Networks-based optimization of shallow machine learning (ML) classifiers

Kaizhu Huang, Amir Hussain, Summrina Kanwal, 2021, Expert Syst. Appl..

Stochastic Conjugate Gradient Algorithm With Variance Reduction

Kaizhu Huang, Xu-Yao Zhang, Xiao-Bo Jin, 2017, IEEE Transactions on Neural Networks and Learning Systems.

Integrated Discovery of Location Prediction Rules in Mobile Environment

Kaizhu Huang, Xiaolong Xu, Nektarios Georgalas, 2017, 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech).

Learning ECOC and Dichotomizers Jointly from Data

Kaizhu Huang, Cheng-Lin Liu, Guoqiang Zhong, 2010, ICONIP.

Pay Attention Selectively and Comprehensively: Pyramid Gating Network for Human Pose Estimation without Pre-training

Kaizhu Huang, Jimin Xiao, Shufei Zhang, 2020, ACM Multimedia.

Manifold Adversarial Learning pdf

Yang Liu, Kaizhu Huang, Jianke Zhu, 2018, ArXiv.

Knowledge base enrichment by relation learning from social tagging data

Kaizhu Huang, Frans Coenen, Hang Dong, 2020, Inf. Sci..

Biased Minimax Probability Machine for Medical Diagnosis

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

Learning maximum likelihood semi-naive Bayesian network classifier

Kaizhu Huang, Michael R. Lyu, Irwin King, 2002, IEEE International Conference on Systems, Man and Cybernetics.

MTC: A Fast and Robust Graph-Based Transductive Learning Method

Kaizhu Huang, Cheng-Lin Liu, Guanggang Geng, 2015, IEEE Transactions on Neural Networks and Learning Systems.

LEARNING ADVERSARIAL EXAMPLES WITH RIEMANNIAN GEOMETRY

Kaizhu Huang, Amir Hussain, Rui Zhang, 2018 .

Convex ensemble learning with sparsity and diversity

Kaizhu Huang, Chun Yang, Xu-Cheng Yin, 2014, Inf. Fusion.

Degraded Character Recognition by Complementary Classifiers Combination

Jun Sun, Yoshinobu Hotta, Satoshi Naoi, 2007 .

Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances

Kaizhu Huang, Rui Zhang, Ali Raza, 2019, BICS.

Primitives Generation Policy Learning without Catastrophic Forgetting for Robotic Manipulation

Kaizhu Huang, Zhiyong Liu, Amir Hussain, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

Degraded Character Recognition by Complementary Classifiers Combination

Yoshinobu Hotta, Satoshi Naoi, Kaizhu Huang, 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

Self-focus Deep Embedding Model for Coarse-Grained Zero-Shot Classification

Kaizhu Huang, Rui Zhang, Amir Hussain, 2019, BICS.

Context-Aware Human Activity and Smartphone Position-Mining with Motion Sensors

Dawei Liu, Kaizhu Huang, Zhiqiang Gao, 2019, Remote. Sens..

Improve Deep Learning with Unsupervised Objective

Rui Zhang, Kaizhu Huang, Amir Hussain, 2017, ICONIP.

Learning classifiers from imbalanced data based on biased minimax probability machine

Kaizhu Huang, Michael R. Lyu, Irwin King, 2004, CVPR 2004.

Sparse learning for support vector classification

Yoshinobu Hotta, Satoshi Naoi, Kaizhu Huang, 2010, Pattern Recognit. Lett..

Hybrid Channel Based Pedestrian Detection

Kaizhu Huang, William Zhu, Mingjian Chen, 2020, Neurocomputing.

Kernel Maximum a Posteriori Classification with Error Bound Analysis

Zenglin Xu, Michael R. Lyu, Kaizhu Huang, 2007, ICONIP.

Two-layer Mixture of Factor Analyzers with Joint Factor Loading

Rui Zhang, Kaizhu Huang, Xi Yang, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Approximately optimizing NDCG using pair-wise loss

Kaizhu Huang, Guo-Sen Xie, Xiao-Bo Jin, 2018, Inf. Sci..

Graphical Lasso Quadratic Discriminant Function for Character Recognition

Satoshi Naoi, Bo Xu, Kaizhu Huang, 2011, ICONIP.

Mining human activity and smartphone position from motion sensors

Yi Huang, Dawei Liu, Kaizhu Huang, 2019, IUI Companion.

Special Issue Editorial: Cognitively-Inspired Computing for Knowledge Discovery

Rui Zhang, Xiaobo Jin, Kaizhu Huang, 2018, Cognitive Computation.

Combination of Classification and Clustering Results with Label Propagation

Kaizhu Huang, Cheng-Lin Liu, Xu-Yao Zhang, 2014, IEEE Signal Processing Letters.

MPSSD: Multi-Path Fusion Single Shot Detector

Kaizhu Huang, Amir Hussain, Yannis Goulermas, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Constructing a large node Chow-Liu tree based on frequent itemsets

Kaizhu Huang, Michael R. Lyu, Irwin King, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Hybrid Metaheuristic Algorithms: Past, Present, and Future

Xin-She Yang, Kaizhu Huang, T. O. Ting, 2015, Recent Advances in Swarm Intelligence and Evolutionary Computation.

A Handwritten Chinese Address Recognition Method Using Recursive Holistic Word Matching and Edit Distance Based Verification Strategies

Yoshinobu Hotta, Satoshi Naoi, Kaizhu Huang, 2006 .

An SVM-Based High-accurate Recognition Approach for Handwritten Numerals by Using Difference Features

Yoshinobu Hotta, Satoshi Naoi, Kaizhu Huang, 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

One-Side Probability Machine: Learning Imbalanced Classifiers Locally and Globally

Rui Zhang, Kaizhu Huang, 2013, ICONIP.

Maxi-Min discriminant analysis via online learning

Bo Xu, Kaizhu Huang, Cheng-Lin Liu, 2012, Neural Networks.

Semi-supervised Learning from General Unlabeled Data

Zenglin Xu, Michael R. Lyu, Kaizhu Huang, 2008, 2008 Eighth IEEE International Conference on Data Mining.

A multi-task framework for metric learning with common subspace

Kaizhu Huang, Cheng-Lin Liu, Peipei Yang, 2012, Neural Computing and Applications.

Local Support Vector Regression for Financial Time Series Prediction

Michael R. Lyu, Kaizhu Huang, Irwin King, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Joint learning of error-correcting output codes and dichotomizers from data

Kaizhu Huang, Cheng-Lin Liu, Guoqiang Zhong, 2011, Neural Computing and Applications.

A novel classifier ensemble method with sparsity and diversity

Kaizhu Huang, Xu-Cheng Yin, Hongwei Hao, 2014, Neurocomputing.

Adversarial Rectification Network for Scene Text Regularization

Rui Zhang, Kaizhu Huang, Jing Li, 2020, ICONIP.

A Rock Structure Recognition System Using FMI Images

Qian Liu, Kaizhu Huang, Xu-Cheng Yin, 2009, ICONIP.

The Minimum Error Minimax Probability Machine

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

Fine-Grained Image Classification with Object-Part Model

Kaizhu Huang, Rui Zhang, Xinheng Wang, 2019, BICS.

Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques

Kaizhu Huang, Amir Hussain, Wadii Boulila, 2016, 2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC).

Siamese network ensemble for visual tracking

Kaizhu Huang, Tammam Tillo, Jimin Xiao, 2018, Neurocomputing.

Special issue on advances in graph algorithm and applications

Kaizhu Huang, Cheng-Lin Liu, Zhi-Yong Liu, 2019, Neurocomputing.

Multiple Outlooks Learning with Support Vector Machines

Kaizhu Huang, Cheng-Lin Liu, Xu-Yao Zhang, 2012, ICONIP.

Localized support vector regression for time series prediction

Michael R. Lyu, Kaizhu Huang, Irwin King, 2009, Neurocomputing.

Novel deep neural network based pattern field classification architectures

Kaizhu Huang, Rui Zhang, Amir Hussain, 2020, Neural Networks.

Segmentation Mask Guided End-to-End Person Search pdf

Yao Zhao, Kaizhu Huang, Jimin Xiao, 2020, Signal Process. Image Commun..

Robust Text Detection in Natural Scene Images

Kaizhu Huang, Xu-Cheng Yin, Xuwang Yin, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Deep Mixtures of Factor Analyzers with Common Loadings: A Novel Deep Generative Approach to Clustering

Rui Zhang, Kaizhu Huang, Xi Yang, 2017, ICONIP.

Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings

Kaizhu Huang, Amir Hussain, Huimin Zhao, 2020, International Conference on Advances in Brain Inspired Cognitive Systems.

Learning Latent Features With Infinite Nonnegative Binary Matrix Trifactorization

Rui Zhang, Xi Yang, Kaizhu Huang, 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.

Improving Script Identification by Integrating Text Recognition Information

Rui Zhang, Kaizhu Huang, Jing Li, 2019, Aust. J. Intell. Inf. Process. Syst..

Learning Locality Preserving Graph from Data

Kaizhu Huang, Cheng-Lin Liu, Xinwen Hou, 2014, IEEE Transactions on Cybernetics.

Enhanced LSTM with Batch Normalization

Kaizhu Huang, Guoqiang Zhong, Shoujun Yan, 2019, ICONIP.

Ellipse Detection with an Improved Randomized Hough Transform for Intellectual Phacoemulsification Surgery Systems

Qian Liu, Kaizhu Huang, Xu-Cheng Yin, 2010, ICIP.

Fast kNN Graph Construction with Locality Sensitive Hashing

Kaizhu Huang, Cheng-Lin Liu, Guanggang Geng, 2013, ECML/PKDD.

Fast and Robust Graph-based Transductive Learning via Minimum Tree Cut

Kaizhu Huang, Cheng-Lin Liu, Yan-Ming Zhang, 2011, 2011 IEEE 11th International Conference on Data Mining.

A Scenario-View Based Approach to Analyze External Behavior of Web Services for Supporting Mediated Service Interactions

Lei Shu, Kaizhu Huang, Manfred Hauswirth, 2008, 2008 IEEE International Conference on Services Computing.

DE2: Dynamic ensemble of ensembles for learning nonstationary data

Kaizhu Huang, Xu-Cheng Yin, Hongwei Hao, 2015, Neurocomputing.

IAN: The Individual Aggregation Network for Person Search

Yunchao Wei, Kaizhu Huang, Jiashi Feng, 2017, Pattern Recognit..

Maximum margin semi-supervised learning with irrelevant data

Kaizhu Huang, Irwin King, Haiqin Yang, 2015, Neural Networks.

Neural Information Processing

Kaizhu Huang, Kok Wai Wong, Andrew Teoh, 2014, Lecture Notes in Computer Science.

Pattern Field Classification with Style Normalized Transformation

Kaizhu Huang, Cheng-Lin Liu, Xu-Yao Zhang, 2011, IJCAI.

Generalized Adversarial Training in Riemannian Space

Kaizhu Huang, Rui Zhang, Amir Hussain, 2019, Industrial Conference on Data Mining.

Multi-modal Adversarial Training for Crisis-related Data Classification on Social Media

Kaizhu Huang, Frans Coenen, Wei Wang, 2020, 2020 IEEE International Conference on Smart Computing (SMARTCOMP).

An efficient post-processing approach for off-line handwritten chinese address recognition

Kaizhu Huang, Chong Long, Xiaoyan Zhu, 2006, 2006 8th international Conference on Signal Processing.

Exchange Rate Forecasting Using Classifier Ensemble

Qian Liu, Kaizhu Huang, Xu-Cheng Yin, 2009, ICONIP.

Direct Zero-Norm Optimization for Feature Selection

Michael R. Lyu, Kaizhu Huang, Irwin King, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Deep Minimax Probability Machine

Zenglin Xu, Kaizhu Huang, Lirong He, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

Joint Learning of Unsupervised Dimensionality Reduction and Gaussian Mixture Model

Rui Zhang, Kaizhu Huang, Xi Yang, 2017, Neural Processing Letters.

Improving deep neural network performance by integrating kernelized Min-Max objective

Rui Zhang, Kaizhu Huang, Amir Hussain, 2020, Neurocomputing.

Neural CAPTCHA networks

Kaizhu Huang, Guoqiang Zhong, Ying Ma, 2020 .

Improving Image Caption Performance with Linguistic Context

Kaizhu Huang, Rui Zhang, Qiu-Feng Wang, 2019, BICS.

Action Recognition in Videos with Temporal Segments Fusions

Kaizhu Huang, Rui Zhang, Qiu-Feng Wang, 2019, BICS.

An Interactive and Generative Approach for Chinese Shanshui Painting Document

Kaizhu Huang, Cheng-Hung Lo, Qiu-Feng Wang, 2019, 2019 International Conference on Document Analysis and Recognition (ICDAR).

Generalized sparse metric learning with relative comparisons

Kaizhu Huang, Colin Campbell, Yiming Ying, 2011, Knowledge and Information Systems.

Encoding primitives generation policy learning for robotic arm to overcome catastrophic forgetting in sequential multi-tasks learning

Kaizhu Huang, Amir Hussain, Hong Qiao, 2020, Neural Networks.

Automated Social Text Annotation With Joint Multilabel Attention Networks

Kaizhu Huang, Frans Coenen, Wei Wang, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Finite Mixture Model of Bounded Semi-naive Bayesian Networks Classifier

Michael R. Lyu, Kaizhu Huang, Irwin King, 2003, ICANN.

A new two-layer mixture of factor analyzers with joint factor loading model for the classification of small dataset problems

Kaizhu Huang, Rui Zhang, Amir Hussain, 2018, Neurocomputing.

A fast projected fixed-point algorithm for large graph matching

Yao Lu, Kaizhu Huang, Cheng-Lin Liu, 2012, Pattern Recognit..

Efficient clinical decision making by learning from missing clinical data

Kaizhu Huang, Amir Hussain, Warner V. Slack, 2013, 2013 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE).

Adaptive modeling for large-scale advertisers optimization

Kaizhu Huang, Song Li, Wei Yu, 2017 .

Accurate and robust text detection: a step-in for text retrieval in natural scene images

Kaizhu Huang, Xu-Cheng Yin, Hongwei Hao, 2013, SIGIR.

Accelerating Infinite Ensemble of Clustering by Pivot Features

Kaizhu Huang, Amir Hussain, Guo-Sen Xie, 2018, Cognitive Computation.

Discriminant Zero-Shot Learning with Center Loss

Kaizhu Huang, Guo-Sen Xie, Xiao-Bo Jin, 2019, Cognitive Computation.

Low Rank Metric Learning with Manifold Regularization

Kaizhu Huang, Cheng-Lin Liu, Guoqiang Zhong, 2011, 2011 IEEE 11th International Conference on Data Mining.

Bo Xu, Kaizhu Huang, Cheng-Lin Liu, 2010, 2010 12th International Conference on Frontiers in Handwriting Recognition.

Super-resolving Tiny Faces with Face Feature Vectors

Kaizhu Huang, Yangkai Luo, Kaizhu Huang, 2020, 2020 10th International Conference on Information Science and Technology (ICIST).

Imbalanced learning with a biased minimax probability machine

Kaizhu Huang, Irwin King, Haiqin Yang, 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Robust Metric Learning by Smooth Optimization

Zenglin Xu, Rong Jin, Kaizhu Huang, 2010, UAI.

Efficient Minimax Clustering Probability Machine by Generalized Probability Product Kernel

Michael R. Lyu, Kaizhu Huang, Irwin King, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Reducing and Stretching Deep Convolutional Activation Features for Accurate Image Classification

Kaizhu Huang, Junyu Dong, Guoqiang Zhong, 2018, Cognitive Computation.

Feature Representation Matters: End-to-End Learning for Reference-Based Image Super-Resolution

Mingjie Sun, Kaizhu Huang, Jimin Xiao, 2020, ECCV.

On Model Robustness Against Adversarial Examples pdf

Zenglin Xu, Kaizhu Huang, Shufei Zhang, 2019, ArXiv.

Learning classifiers from imbalanced data based on biased minimax probability machine

Michael R. Lyu, Kaizhu Huang, Irwin King, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Field Support Vector Regression

Rui Zhang, Kaizhu Huang, Haochuan Jiang, 2017, ICONIP.

Multicores and GPU utilization in parallel swarm algorithm for parameter estimation of photovoltaic cell model

Kaizhu Huang, Kyeong Soo Kim, Tiew On Ting, 2016, Appl. Soft Comput..

Learning Imbalanced Classifiers Locally and Globally with One-Side Probability Machine

Kaizhu Huang, Rui Zhang, Xu-Cheng Yin, 2014, Neural Processing Letters.

Improving Deep Neural Network Performance with Kernelized Min-Max Objective

Rui Zhang, Kaizhu Huang, Amir Hussain, 2018, ICONIP.

Semi-supervised text categorization by active search

Zenglin Xu, Rong Jin, Michael R. Lyu, 2008, CIKM '08.

Generative adversarial networks with mixture of t-distributions noise for diverse image generation

Kaizhu Huang, Guoqiang Zhong, Yongbin Liu, 2019, Neural Networks.

Is DeCAF Good Enough for Accurate Image Classification?

Kaizhu Huang, Junyu Dong, Guoqiang Zhong, 2015, ICONIP.

Learning from data locally and globally

Kaizhu Huang, Kaizhu Huang, 2004 .

Joint Multi-Label Attention Networks for Social Text Annotation

Hang Dong, Kaizhu Huang, Frans Coenen, 2019, NAACL.

Learning from Few Samples with Memory Network

Kaizhu Huang, Shufei Zhang, 2016, ICONIP.

Learning from Few Samples with Memory Network

Rui Zhang, Kaizhu Huang, Amir Hussain, 2016, Cognitive Computation.

Maximizing sensitivity in medical diagnosis using biased minimax probability Machine

Michael R. Lyu, Kaizhu Huang, Irwin King, 2006, IEEE Transactions on Biomedical Engineering.

Introduction to Deep Density Models with Latent Variables

Rui Zhang, Kaizhu Huang, Amir Hussain, 2019, Cognitive Computation Trends.

Geometry preserving multi-task metric learning

Kaizhu Huang, Cheng-Lin Liu, Peipei Yang, 2012, Machine Learning.

GSML: A Unified Framework for Sparse Metric Learning

Kaizhu Huang, Colin Campbell, Yiming Ying, 2009, 2009 Ninth IEEE International Conference on Data Mining.

FMI image based rock structure classification using classifier combination

Qian Liu, Kaizhu Huang, Xu-Cheng Yin, 2011, Neural Computing and Applications.

Approximate kNN graph construction with locality sensitive hashing

Cheng-Lin Liu, Kaizhu Huang, Guanggang Geng, 2013 .

Cross-modality interactive attention network for multispectral pedestrian detection

Hong Qiao, Kaizhu Huang, Amir Hussain, 2019, Inf. Fusion.

Maximum Power Point Estimation for Photovoltaic Strings Subjected to Partial Shading Scenarios

Kaizhu Huang, Huiqing Wen, Jieming Ma, 2019, IEEE Transactions on Industry Applications.

Dynamic Ensemble of Ensembles in Nonstationary Environments

Kaizhu Huang, Xu-Cheng Yin, Hongwei Hao, 2013, ICONIP.

PointNu-Net: Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification in the Clinical Wild pdf

Kaizhu Huang, Amir Hussain, Kai Yao, 2021, ArXiv.

Multi-modal generative adversarial networks for traffic event detection in smart cities

Kaizhu Huang, Frans Coenen, Suparna De, 2021, Expert Syst. Appl..

Scaffold-A549: A Benchmark 3D Fluorescence Image Dataset for Unsupervised Nuclei Segmentation

Kaizhu Huang, Jie Sun, Curran Jude, 2021, Cognitive Computation.

Improving Model Robustness with Latent Distribution Locally and Globally pdf

Kaizhu Huang, Xinping Yi, Shufei Zhang, 2021, ArXiv.

Coarse-grained generalized zero-shot learning with efficient self-focus mechanism

Kaizhu Huang, Amir Hussain, Guanyu Yang, 2021, Neurocomputing.

Towards Better Robust Generalization with Shift Consistency Regularization

Kaizhu Huang, Xinping Yi, Shufei Zhang, 2021, ICML.

A Covert Ultrasonic Phone-to-Phone Communication Scheme

Kaizhu Huang, Xinheng Wang, Liming Shi, 2020, International Conference on Collaborative Computing.

Manifold adversarial training for supervised and semi-supervised learning

Kaizhu Huang, Jianke Zhu, Shufei Zhang, 2021, Neural Networks.

Improving generative adversarial networks with simple latent distributions

Rui Zhang, Kaizhu Huang, Amir Hussain, 2021, Neural Computing and Applications.

Mix-Up Augmentation for Oracle Character Recognition with Imbalanced Data Distribution

Kaizhu Huang, Jing Li, Rui Zhang, 2021, IEEE International Conference on Document Analysis and Recognition.

FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizer by Strong Convexity pdf

Kaizhu Huang, Yangfan Zhou, Cheng Cheng, 2021, ArXiv.

LGD-GCN: Local and Global Disentangled Graph Convolutional Networks pdf

Kaizhu Huang, Xinping Yi, Rui Zhang, 2021, ArXiv.

Structure First Detail Next: Image Inpainting with Pyramid Generator pdf

Kaizhu Huang, Yinghui Xu, Matan Protter, 2021, 2023 IEEE International Conference on Multimedia and Expo (ICME).

Attention-Augmented Machine Memory

Qingyang Li, Kaizhu Huang, Guoqiang Zhong, 2021, Cognitive Computation.

Reborn Mechanism: Rethinking the Negative Phase Information Flow in Convolutional Neural Network pdf

Kaizhu Huang, Chenglei Peng, Zhicheng Cai, 2021, ArXiv.

Domain adaptation with feature and label adversarial networks

Zenglin Xu, Kaizhu Huang, Zhao Kang, 2021, Neurocomputing.

Each Attribute Matters: Contrastive Attention for Sentence-based Image Editing pdf

Kaizhu Huang, Fan Lyu, Fenglei Xu, 2021, BMVC.

Disentangling Semantic-to-Visual Confusion for Zero-Shot Learning pdf

Kaizhu Huang, Zihan Ye, Fan Lyu, 2021, IEEE Transactions on Multimedia.

FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity

Kaizhu Huang, Amir Hussain, Yangfan Zhou, 2021 .

A Systematic Analysis of Link Prediction in Complex Network

Kaizhu Huang, Awais Adnan, Haji Gul, 2021, IEEE Access.

Three-Dimensional Local Energy-Based Shape Histogram ( 3 D-LESH )-Based Feature Extraction – A Novel Technique

Kaizhu Huang, Summrina Kanwal Wajid, Kaizhu Huang, 2017 .

Discriminative Naive Bayesian Classifiers

Kaizhu Huang, .

Finite Mixture Model of Bounded Semi-Naive Bayesian Networks for Classification

Kaizhu Huang, Michael R. Lyu, Irwin King, 2003 .