Huanhuan Chen

According to our database1, Huanhuan Chen authored at least 60 papers between 2004 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
An Automatic GPR B-Scan Image Interpreting Model.
IEEE Trans. Geoscience and Remote Sensing, 2018

Sequential data classification by dynamic state warping.
Knowl. Inf. Syst., 2018

Ensemble Pruning based on Objection Maximization with a General Distributed Framework.
CoRR, 2018

Disturbance Grassmann Kernels for Subspace-Based Learning.
CoRR, 2018

Disturbance Grassmann Kernels for Subspace-Based Learning.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Balancing exploration and exploitation in multiobjective evolutionary optimization.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

2017
Scalable Graph-Based Semi-Supervised Learning through Sparse Bayesian Model.
IEEE Trans. Knowl. Data Eng., 2017

A Cluster-Based Semisupervised Ensemble for Multiclass Classification.
IEEE Trans. Emerging Topics in Comput. Intellig., 2017

Optimal relay placement for lifetime maximization in wireless underground sensor networks.
Inf. Sci., 2017

Gesture segmentation based on a two-phase estimation of distribution algorithm.
Inf. Sci., 2017

Dynamic State Warping.
CoRR, 2017

Knowledge Engineering With Big Data (BigKE): A 54-Month, 45-Million RMB, 15-Institution National Grand Project.
IEEE Access, 2017

A predictive performance comparison of machine learning models for judicial cases.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Understanding Data Partition for Applications on CPU-GPU Integrated Processors.
Proceedings of the Mobile Ad-hoc and Sensor Networks - 13th International Conference, 2017

An Effective Martin Kernel for Time Series Classification.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

Granger Causality for Multivariate Time Series Classification.
Proceedings of the IEEE International Conference on Big Knowledge, 2017

Revisit Word Embeddings with Semantic Lexicons for Modeling Lexical Contrast.
Proceedings of the IEEE International Conference on Big Knowledge, 2017

2016
Defect- and Variation-Tolerant Logic Mapping in Nanocrossbar Using Bipartite Matching and Memetic Algorithm.
IEEE Trans. VLSI Syst., 2016

Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond.
IEEE Trans. Neural Netw. Learning Syst., 2016

A decentralized quantum-inspired particle swarm optimization algorithm with cellular structured population.
Inf. Sci., 2016

Probabilistic Feature Selection and Classification Vector Machine.
CoRR, 2016

Sequential Data Classification in the Space of Liquid State Machines.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Improve Chinese Word Embeddings by Exploiting Internal Structure.
Proceedings of the NAACL HLT 2016, 2016

Model-Based Oversampling for Imbalanced Sequence Classification.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
A New Evolutionary Algorithm with Structure Mutation for the Maximum Balanced Biclique Problem.
IEEE Trans. Cybernetics, 2015

The Benefits of Modeling Slack Variables in SVMs.
Neural Computation, 2015

Robust twin boosting for feature selection from high-dimensional omics data with label noise.
Inf. Sci., 2015

Knowledge Engineering with Big Data.
IEEE Intelligent Systems, 2015

Model Metric Co-Learning for Time Series Classification.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014
Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection.
IEEE Trans. Neural Netw. Learning Syst., 2014

Learning in the Model Space for Cognitive Fault Diagnosis.
IEEE Trans. Neural Netw. Learning Syst., 2014

Pre-Silicon Bug Forecast.
IEEE Trans. on CAD of Integrated Circuits and Systems, 2014

Combining learning in model space fault diagnosis with data validation/reconstruction: Application to the Barcelona water network.
Eng. Appl. of AI, 2014

Cognitive fault diagnosis in Tennessee Eastman Process using learning in the model space.
Computers & Chemical Engineering, 2014

Learning the deterministically constructed Echo State Networks.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Support Vector Ordinal Regression using Privileged Information.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Sparse Bayesian approach for feature selection.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Big Data, 2014

2013
Model-based kernel for efficient time series analysis.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012
Semisupervised Classification With Cluster Regularization.
IEEE Trans. Neural Netw. Learning Syst., 2012

Learning in the Model Space for Fault Diagnosis
CoRR, 2012

EEG Based Foot Movement Onset Detection with the Probabilistic Classification Vector Machine.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

Neural Network Ensembles to Determine Growth Multi-classes in Predictive Microbiology.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

2011
Semi-supervised learning with extremely sparse labeled data on multiple semi-supervised assumptions.
Proceedings of the Third International Conference of Soft Computing and Pattern Recognition, 2011

Buried Utility Pipeline Mapping Based on Multiple Spatial Data Sources: A Bayesian Data Fusion Approach.
Proceedings of the IJCAI 2011, 2011

2010
Multiobjective Neural Network Ensembles Based on Regularized Negative Correlation Learning.
IEEE Trans. Knowl. Data Eng., 2010

Negative correlation learning for classification ensembles.
Proceedings of the International Joint Conference on Neural Networks, 2010

Probabilistic robust hyperbola mixture model for interpreting ground penetrating radar data.
Proceedings of the International Joint Conference on Neural Networks, 2010

Buried Utility Pipeline Mapping based on Street Survey and Ground Penetrating Radar.
Proceedings of the ECAI 2010, 2010

2009
Regularized Negative Correlation Learning for Neural Network Ensembles.
IEEE Trans. Neural Networks, 2009

Probabilistic Classification Vector Machines.
IEEE Trans. Neural Networks, 2009

Predictive Ensemble Pruning by Expectation Propagation.
IEEE Trans. Knowl. Data Eng., 2009

Evolving Least Squares Support Vector Machines for Stock Market Trend Mining.
IEEE Trans. Evolutionary Computation, 2009

Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning.
Proceedings of the Artificial Neural Networks, 2009

2007
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity.
Proceedings of the Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 2007

Evolutionary random neural ensembles based on negative correlation learning.
Proceedings of the IEEE Congress on Evolutionary Computation, 2007

2006
Trade-Off Between Diversity and Accuracy in Ensemble Generation.
Proceedings of the Multi-Objective Machine Learning, 2006

A Probabilistic Ensemble Pruning Algorithm.
Proceedings of the Workshops Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

Evolutionary Multiobjective Ensemble Learning Based on Bayesian Feature Selection.
Proceedings of the IEEE International Conference on Evolutionary Computation, 2006

2004
Quantum secure circuit evaluation.
Science in China Series F: Information Sciences, 2004

HW-SW partitioning based on genetic algorithm.
Proceedings of the IEEE Congress on Evolutionary Computation, 2004


  Loading...