Data Analytics & Complex Systems Publications

C-RT1.1

  1. Thanh Tuan, Benjamin BIGOT, Eng Siong CHNG. “Speech Enhancement Using Beamforming And Non Negative Matrix Factorization For Robust Speech Recognition In The Chime-3 Challenge”. In Proceedings of 2015 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2015) , Scottsdale, Arizona, USA, December 13-17, 2015
  2. Vu THANH, Benjamin BIGOT and Eng Siong CHNG. Combining Deep Neural Networks and Non negative Matrix Factorization for Speech Enhancement and Automatic Speech Recognition. in 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016)
  3. Yerbolat Khassanov, Tze Yuang Chong, Benjamin Bigot, Eng Siong Chng, “Unsupervised Language Model Adaptation by Data Selection for Speech Recognition”, Asian Conference on Intelligent Information and Database Systems (ACCIDS 2017), 3-5 April 2017, Kanazawa, Japan.

C-RT1.2

  1. Yukun MA, Jung-jae Kim,Benjamin Bigot, Tahir KHAN. Feature Enriched Word Embedding for NER in Conversational Speech. 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016)
  2. Muhammad Tahir KHAN, Yukun MA, Jung-jae Kim. Term Ranker: A Graph-Based Re-Ranking Approach. Proceedings of the 2016 International Flairs Conference (FLAIRS-29), Florida, USA.
  3. Yukun MA, GAO Sa, Erik CAMBRIA, “Label Embedding for Zero-shot Fine-grained Named Entity Typing”, 26th International Conference on Computational Linguistics (COLING), Osaka, Japan, 11-16 December 2016
  4. Ceyda Sanli, Anupam Mondal, and Erik Cambria, “Tracing Linguistic Relations in Winning and Losing Sides of Explicit Opposing Groups”, The 30th International FLAIRS Conference (The Florida Artificial Intelligence Research Society), on May 22-24, 2017, Marco Island, Florida, USA.
  5. Yukun MA, Benjamin BIGOT, Erik CAMBRIA, “ASR hypothesis reranking using prior-informed restricted Boltzmann machine”, 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), on April 17-23, 2017, Budapest, Hungary.

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C-RT2.1

  1. W. H. CHAI, S.-S. HO, and C.K. GOH, “Exploiting sparsity for image-based object surface anomaly detection,” in 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016)
  2. Patrick Chen Pei-Hung and Shen-Shyang Ho, “Is OVERFEAT Useful for Image-based Surface Defect Classification Task?”, 23rd IEEE International Conference on Image Processing, Phoenix, Arizona, USA, September 25-28, 2016.
  3. Woon Huei Chai, Chi-Keong Goh, Shen-Shyang Ho, and Hiok Chai Quek, “A Fast Sparse Reconstruction Approach For High Dimensional Image-Based Object Surface Anomaly Detection”,15th IAPR International Conference on Machine Vision Applications, Nagoya, Japan, May 2017

C-RT2.2

  1. Siyi Pan, Tzu-Yi Hung, Liang-Tien Chia, Using Material Classification Methods for Steel Surface Defect Inspection, 25rd IEEE International Symposium on Industrial Electronics, Santa Clara, CA, USA, June 8-10, 2016.
  2. Sriram Vaikundam, Tzu-Yi Hung, Liang-Tien Chia, Anomaly Region Detection and Localization in Metal Surface Inspection, 23rd IEEE International Conference on Image Processing, Phoenix, Arizona, USA, September 25-28, 2016.
  3. Tzu-Yi Hung, Sriram Vaikundam, Vidhya Natarajan, Liang-Tien Chia, Phase Fourier Reconstruction for Anomaly Detection on Metal Surface Using Salient Irregularity, 23rd International Conference on Multimedia Modeling, Reykjavik, Iceland, January 4-6, 2017.
  4. Vidhya Natarajan, Tzu-Yi Hung, Sriram Vaikundam, Liang-Tien Chia, Convolutional Networks for Voting-based Anomaly Classification in Metal Surface Inspection, 18th Annual International Conference on Industrial Technology, Toronto, Canada, March 22-25, 2017.

C-RT3.1

  1. A.T.W. Min, R. Sagarna, A. Gupta, O.Y. Soon and C.K. Goh, “Knowledge Transfer through Machine Learning in Aircraft Design”, Computational Intelligence Magazine. (Data set associated with this paper is available here: http://blogs.ntu.edu.sg/rr-ntucorplab/enginesim_data-2l7x6gq/ )
  2. Bingshui Da, Abhishek Gupta, Yew-Soon Ong, Liang Feng, Puay-Siew Tan. The Boom of Gene-Culture Interaction for Effective Evolutionary Multitasking. Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), 2-5 February 2016, Canberra, Australia.
  3. Wan-Yu Deng, Yew-Soon Ong, Qing-Hua Zheng. A Fast Reduced Kernel Extreme Learning Machine. Neural Networks. 2015.
  4. A. Gupta, J. Mandziuk, Y-S Ong, “Evolutionary Multitasking in Bi-Level Optimization”, Complex & Intelligent Systems, Vol. 1, pp. 83-95, Feb 2016.
  5. Y.ZHAI, Y-S Ong, and I. W. Tsang, “Making Trillion Correlations Feasible in Feature Grouping and Selection”, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 23 Feb 2016.
  6. A. Gupta, Y-S Ong, L. Feng, K. C. Tan, “Multi-Objective Multifactorial Optimization in evolutionary Multitasking”, IEEE Transactions on Cybernetics, May 2016.
  7. A. Gupta, Y-S Ong, P. A. Kelly, C. K. Goh, “Pareto Rank Learning for Multi-Objective Bi-Level Optimization: A Study in Composites Manufacturing”, 2016 IEEE World Congress on Computational Intelligence, Vancouver, Canada, July 2016.
  8. A. Gupta, Y-S Ong, B. Da, L. Feng, D. Handoko, “Measuring Complementarity between Function Landscapes in Evolutionary Multitasking”, 2016 IEEE World Congress on Computational Intelligence, Vancouver, Canada, July 2016.
  9. P. Wei, Y. Ke, C-K Goh, “Deep Nonlinear Feature Coding for Unsupervised Domain Adaptation”, 2016 International Joint Conference on Artificial Intelligence, New Work, USA, July 2016.
  10. R. Chandra, A. Gupta, Y-S Ong and C-K. Goh, “Evolutionary multi-task learning for modular training of feedforward neural networks”, 23rd International Conference on Neural Information Processing, Kyoto, Japan, October 16-21, 2016.
  11.  R. Sagarna, Y-S Ong, “Concurrently Searching Branches in Software Tests Generation through Multitask Evolution”, 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, December 6-9, 2016.
  12. Y. Liu, X. Li, A. W-K Kong, C-K Goh, “Learning from small data: a pairwise approach for ordinal regression”, 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, December 6-9, 2016.
  13. D. Lim, Y-S Ong, A. Gupta, C.K. Goh, P. Dutta, “Towards A New Praxis in Optinformatics for Evolutionary Computation: Simultaneous Problem Learning and Optimization”, Evolutionary Intelligence, Sep 2016.
  14. A.T.W. Min,  R. Sagarna, A. Gupta, R. Chandra, and Y-S Ong, “Coping with Data Scarcity in Aircraft Engine Design”, AIAA AVIATION 2017, Denver, Colorado, USA, 5–9 June 2017
  15. Y. LiuA. W-K Kong and C-K Goh, “Deep Ordinal Regression based on Data Relationship for Small Datasets”, Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, Australia, 19-25 August 2017
  16. P. Wei,  R. Sagarna, Y. Ke, Y-S Ong and C-K Goh, “Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression”, 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia, 6 – 11 August, 2017

C-RT3.2

  1. Yan Chao Wang, Qian Zhang, Feng Lin, Chi Keong Goh, Xuan Wang and Hock Soon Seah, “Histogram Equalization and Specification for High-dimensional Data Visualization using RadViz”, Computer Graphics International 2017, 27-30 June 2017, Japan.

C-RT3.5

  1. H. Yang, J. T. Zhou and J. Cai, “Improving multi-label learning with missing labels by structured semantic correlations”, The 14th European Conference on Computer Vision (ECCV2016, Oral presentation), Amsterdam, 8-16 October, 2016.
  2. Haitao Liu, Jianfei Cai and Yew-Soon Ong, “An Adaptive Sampling Approach for Kriging Metamodeling by Maximizing Expected Prediction Error”, Computers & Chemical Engineering, 2017.
  3. Haitao Liu, Yew-Soon Ong and Jianfei Cai, “A Survey of Adaptive Sampling for Global Metamodeling in Support of Simulation-based Complex Engineering Design”, Structural and Multidisciplinary Optimization, 2017.

C-RT4.1

  1. D. K. Prasad, C.K. Prasath, D. Rajan, L. Rachmawati, E. Rajabaly, and C. Quek, “Challenges in video based object detection in maritime scenario using computer vision,” 19th International Conference on Connected Vehicles, Zurich, 13-14 January, 2017.
  2. D. K. Prasad, D. Rajan, C.K. Prasath, L. Rachmawati, E. Rajabaly, and C. Quek, “MSCM-LiFe: Multi-scale cross modal linear feature for horizon detection in maritime images,” IEEE TENCON 2016, Singapore, 22-25 November, 2016.
  3. D. K. Prasad, C.K. Prasath, D. Rajan, L. Rachmawati, E. Rajabaly, and C. Quek, “Maritime situational awareness using adaptive multisensory management under hazy conditions,” 5th International Maritime-Port Technology and Development Conference (MTEC 2017), Singapore, 26-28 April, 2017.
  4. D. K. Prasad, D. Rajan, L. Rachmawati, E. Rajabaly, and C. Quek, ” MuSCoWERT: multi-scale consistence of weighted edge Radon transform for horizon detection in maritime images,” JOSA A(OSA), 2016.
  5. D. K. Prasad, D. Rajan, L. Rachmawati, E. Rajabaly, and C. Quek, “Video Processing from Electro-optical Sensors for Object Detection and Tracking in Maritime Environment: A Survey,” IEEE Transactions on Intelligent Transportation Systems (IEEE), 2016.

C-RT4.2

  1. Shaobo Mao, Enmei Tu, Guanghao Zhang, Lily Rachmawati et al.. “An Automatic Identification System (AIS) Database for Maritime Trajectory Prediction and Data Mining”, International Conference on Extreme Learning Machine 2016
  2. Enmei Tu, Guanghao Zhang, Lily Rachmawati et al.. “A Theoretical Study of The Relationship Between An ELM Network and Its Subnetworks”, International Joint Conference on Neural Networks (May 14-19, Alaska, USA)
  3. Enmei Tu, Guanghao Zhang, Lily Rachmawati et al.. “Exploiting AIS data for intelligent maritime navigation: a comprehensive survey”, IEEE Transactions on Intelligent Transportation System
  4. Guanghao Zhang, Enmei Tu, Dongshun Cui. ” STABLE AND IMPROVED GENERATIVE ADVERSARIAL NETS (GANS): A CONSTRUCTIVE SURVEY ” International conference on Image Processing, 2017

C-RT5.1

  1. Moath JARRAH and Jie ZHANG. 2015. Trusted Mediator Agents to Better Manage Complex and Competitive Supply Chains. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS ’15). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1811-1812
  2. Zehong HU, Meng SHA, Moath JARRAH, Jie ZHANG, Hui XI. 2016. Efficient Computation of Emergent Equilibrium in Agent-Based Simulation. Proceedings of The Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Association for the Advancement of Artificial Intelligence, Phoenix, Arizona, USA.
  3. Wen Song, Donghun Kang, Jie Zhang, Hui Xi, “Decentralized Multi-Project Scheduling via Multi-Unit Combinatorial Auction”, Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), 836-844, Singapore, May 2016.
  4. Wen Song, Donghun Kang, Jie Zhang, Hui XI, “A Sampling based Approach for Proactive Project Scheduling with Time-dependent Duration Uncertainty”, submitted and accepted to the 31st AAAI Conference on Artificial Intelligence (AAAI-17).
  5. Wen Song, Donghun Kang, Jie Zhang, Hui Xi, “Proactive Project Scheduling with Time-dependent Workability Uncertainty”, the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 8-12 May, 2017.
  6. Donghun Kang, Zhenchao Bing, Wen Song, Zehong Hu, Shuo Chen, Jie Zhang, Hui Xi, “Automatic Construction of Agent-based Simulation Using Business Process Diagrams and Ontology-based Models”, the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017)(submission date: 23/01/2017).
  7. Zehong Hu, Jie Zhang, “Optimal Posted-Price Mechanism in Microtask Crowdsourcing”, International Joint Conference on Artificial Intelligence (IJCAI 2017)
  8. Wen Song, Donghun Kang, Jie Zhang, Hui Xi, “A Multi-Unit Combinatorial Auction based Approach for Decentralized Multi-Project Scheduling”, Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS)

 C-RT5.2

  1. X. Zhao, Z. Xing, M. A. Kabir, S.-W. Lin, J. Li and N. Sawada, “HDSKG: Harvesting Domain Specific Knowledge Graph from Content of Webpages”, 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER), 20-24 Feb, 2017
  2. M. A. Kabir, Z. Xing, P. Chandrasekaran, S.-W. Lin, “Process Pattern: A Reusable Design Artifact for Business Process Models”, IEEE Computer Society Signature Conference on Computers, Software and Applications (COMSAC 2017), 4-8 July, Torino, Italy, 2017.

 

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