Call for Papers - Special Issue on Machine Learning and Its Applications

Special Issue on Machine Learning and Its Applications

In the last few years machine learning has been one of the most sought-after skills in modern computational science. The core of machine learning deals with representation and generalization.  Representation of data instances and functions evaluated on these instances is a topic poorly discussed in machine learning.  Generalization is the most central concept in machine learning, which will be performed well on unseen data instances.  Generalization has been a key object of study in the subfield of computational learning theory.

Recently, machine learning has attracted close attention of researchers and has also been applied successfully in real-life problems, for example, the areas of administration, commerce, and industry. These successful applications of machine learning in the real-world problems have caused increased interests in learning techniques, dictating further effort in informing people from other disciplines about the art in machine learning and its uses.

The aim of this special issue is to highlight the most significant recent developments on the topics of machine learning and its applications. Contributions containing new insights and findings in this field are welcome. Particular attention will be given to the following theme areas; however, it should be stressed that a broad range of submissions are encouraged. We invite authors to contribute with original research articles as well as review articles to this special issue. Potential topics include, but are not limited to:

  • New benchmarking and evaluation methods for machine learning

  • Convergence proofs for machine learning methods

  • Comparative theoretical and empirical studies on machine learning (e.g. Support Vector Machines, Neural Networks, Gaussian Processes)

  • Machine learning for real-world applications

Important dates (changed Feb. 25th):

Submission deadline: July 1st, 2015
First author notification: Sept. 15th, 2015
Revised version: Nov. 15th, 2015
Final notification: Feb. 1st, 2016


The expected publication time of the special issue will be in spring 2016.
The submission should be addressed to: ybzhyb@163.com


Bin Yu, Dalian Maritime University, Dalian 116024, China; ybzhyb@163.com
Yudong Zhang, Columbia University, New York, USA; zhangyudongnuaa@gmail.com

Dr. Bin YU
Research Scientist, Transportation Management College
Dalian Maritime University, China
Email: ybzhyb@163.com

Dr. Bin YU is a professor of Transportation Management College. His research activity concerns transit system optimization, high performance computing, swarm intelligence and vehicle routing problem. He is internationally known as an active scholar in the field of transportation, with more than 20 papers published in SCI/SSCI indexed journals and an H-index citation rate of 11 (from ISI).

Professional Activities: Membership of Editorial Boards of Journals

  • Editor of PROMET Traffic & Transportation

  • Editor of Scientia Iranica

  • Guest Editor of Transportation Research Part C ("Nature-Inspired Optimization Techniques in Public Transit Planning and Operation")

  • Guest Editor of Transportation Letters: The International Journal of Transportation Research ("Vehicle routing problem")

 Selected Papers published in Journals

[1] YU, Bin, YANG, Zhong-Zhen, LI Shan (2012); Real-Time Partway Deadheading Strategy Based on Transit Service Reliability Assessment. Transportation Research Part A, 46(8): 1265-1279.

[2] YU, Bin, YANG, Zhong-Zhen, JIN, Peng-Huan, WU, Shan-Hua, YAO, Bao-Zhen (2012); Transit route network design-maximizing direct and transfer demand density. Transportation Research Part C, 22:58-75.

[3] Yu, Bin, Lam, William H.K , Tam, Mei Lam (2011); Bus Arrival Time Prediction at Bus Stop with Multiple Routes. Transportation Research Part C, 19(6):1157-1170.

[4] Yu, Bin, Yang, Zhongzhen (2011); An ant colony optimization model: The period vehicle routing problem with time windows. Transportation Research Part E, 47(2):166-181.

[5] Yu, Bin, Yang, Zhongzhen, Yao, Baozhen (2009); An Improved Ant Colony Optimization for Vehicle Routing Problem. European Journal Of Operational Research, 196(1):171-176.

[6] Bin YU, Hanbing ZHU, Wanjun CAI, Ning MA, Baozhen YAO (2013); Two-phase Optimization Approach to Transit Hub Location--the Case of Dalian. Journal of Transport Geography, 33:62-71.

[7] Yu, Bin, Yao, Jinbao, Yang, Zhongzhen (2010); An Improved Headway-based Holding Strategy for Bus Transit. Transportation Planning and Technology, 33(3):329-341.

[8] Yu, Bin, Yang, Zhongzhen and Yao, Baozhen (2006); Bus Arrival Time Prediction Using Support Vector Machines. Journal of Intelligent Transportation Systems, 10(4):151-158.

[9] Yu, Bin, Wu, Shanhua, Yang, Zhongzhen, Yao, Baozhen (2012); Dynamic Vehicle Dispatching at a Transfer Station in Public Transportation System. Journal of Transportation Engineering, 138(2):191-201.

[10] Yu, Bin, Yang, Zhongzhen ,Yao, Jinbao (2010); Genetic Algorithm For Bus Frequency Optimization. Journal of Transportation Engineering, 136(6):576-583.

[11] Yu, Bin, Yang, Zhongzhen, Chen, Kang, Yu, Bo (2010); Hybrid model for prediction of bus arrival times at next station. Journal of Advanced Transportation, 44(3):193-204.

[12] Yu, Bin, Yang, Zhongzhen, Xie, Jingxin (2011); A Parallel Improved Ant Colony Optimization for Multi-depot Vehicle Routing Problem. Journal of The Operational Research Society, 62(1):183-188.

[13] Yu, Bin, Yang, Zhongzhen and Cheng, Chuntian (2007); Optimizing The Distribution Of Shopping Centers With Parallel Genetic Algorithm. Engineering Applications of Artificial Intelligence, 20(2):215-223.

[14] Yu, Bin, Yang, Zhongzhen (2009); A Dynamic Holding Strategy In Public Transit Systems With Real-Time Information. Applied Intelligence, 31(1):69-80.

[14] Yu, Bin, Yang, Zhongzhen, Sun, Xueshan, Yao, Baozhen, Zeng, Qingcheng, Jeppesen, Erik (2011); Parallel Genetic Algorithm in Bus Route Headway Optimization. Applied Soft Computing, 11(8):5081-5091.

[16] Bin YU, Ning MA, Wanjun CAI, Ting LI, Xiaoting YUAN, Baozhen YAO (2013); Improved Ant Colony Optimization for Dynamic Multi-depot Vehicle Routing Problem. International Journal of Logistics Research and Applications, 16(2):144-157.

[17] Bin YU, Ting LI, Hongli BAO, Yahui LI, Baozhen YAO (2013); Real-Time Stop Skipping Strategy for Transit Operations at A Terminal. Road & Transport Research, 22(1):26-38.

[18] Yu, Bin, Yang, Zhongzhen,Wang Jing (2010); Bus travel-time prediction based on bus speed. Proceedings of the Institution of Civil Engineers-Transport, 163(1):3-7.

[19] Yu, Bin, Yang, Zhongzhen ,Yao, Baozhen (2011); A Hybrid Algorithm for Vehicle Routing Problem with Time Windows. Expert Systems with Applications, 38(1):435-441.

[20] Yu, Bin, Yang, Zhongzhen , Yu, Bo (2009); Hybrid Model for Multi-Stop Arrival Time Prediction. Neural Network World, 19(3):321-332.

Dr. Yudong Zhang
Research Scientist, Brain Imaging Lab
Columbia University, USA
Email: zhangyudong@njnu.edu.cn

Dr. Yudong Zhang is Professor of the school of information science and technology at Nanjing Normal University, and adjunct professor of Columbia University since 2013. He received a B.S. from Nanjing University of Aeronautics and Astronautics in 2004, and a M.S. from Nanjing University of Aeronautics and Astronautics in 2007. He received his Ph.D. degree in Signal and Information Processing from Southeast University in 2010. From 2010 to 2012, he worked at Columbia University as a postdoc, and from 2012 to 2013 he worked as an assistant research scientist at Columbia University and NYSPI. His research interests focus on knowledge engineering and MR image processing. He is the author and co-author of 41 SCI-indexed papers.

 Professional Activities: Membership of Editorial Boards of Journals

  • Editor of Fundamenta Informaticae

  • Lead Guest Editor of special issue" Artificial Intelligence and its Applications" of  Mathematical Problems in Engineering

  • Lead Guest Editor of special issue" Swarm Intelligence and Its Applications" of  The Scientific World Journal

  • Lead Guest Editor of special issue" Emerging Trends in Soft Computing Models in Bioinformatics and Biomedicine " of  The Scientific World Journal

  • Lead Guest Editor of special issue" Medical & Biological Imaging " of Sensors

 Selected Papers published in Journals

[1] Suzanne Goh, Zhengchao Dong, Yudong Zhang, Salvatore DiMauro, Bradley S. Peterson. Mitochondrial Dysfunction as a Neurobiological Subtype of Autism Spectrum Disorder: Evidence From Brain Imaging [J]. JAMA Psychiatry. 2014, 71(6): 665-671.

[2] Yudong Zhang, Lenan Wu. Weights Optimization of Neural Network via Improved BCO Approach [J], Progress in Electromagnetics Research, 2008, 83:185-198.

[3] Yudong Zhang, Lenan Wu, Geng Wei. A New Classifier for Polarimetric SAR Images [J]. Progress in Electromagnetics Research. 2009, 94: 83-104

[4] Yudong Zhang, Shuihua Wang, Lenan Wu. A Novel Method for Magnetic Resonance Brain Image Classification based on Adaptive Chaotic PSO [J]. Progress in Electromagnetics Research. 2010, 109: 325-343

[5] Yudong Zhang, Lenan Wu, Shuihua Wang. Magnetic Resonance Brain Image Classification by an Improved Artificial Bee Colony Algorithm [J]. Progress in Electromagnetics Research. 2011, 116: 65-79

[6] Yudong Zhang, Lenan Wu. An MR Brain Images Classifier via Principal Component Analysis and Kernel Support Vector Machine [J]. Progress in Electromagnetics Research. 2012, 130, 369-388

[7] Yudong Zhang*, Shuihua Wang, Zhengchao Dong. Classification of Alzheimer Disease Based on Structural Magnetic Resonance Imaging by Kernel Support Vector Machine Decision Tree [J]. Progress in Electromagnetics Research - Pier. 2014, Vol. 144, 185-191

[8] Yudong Zhang*, Shuihua Wang, Genlin Ji, Zhengchao Dong. An Improved Quality Guided Phase Unwrapping Method and Its Applications to MRI [J]. Progress in Electromagnetics Research - Pier. 2014, 145: 273-286

[9] Yudong Zhang*, Shuihua Wang, Preetha Phillips, Genlin Ji. Binary PSO with Mutation Operator for Feature Selection using Decision Tree applied to Spam Detection [J]. Knowledge-Based Systems. 2014, 64: 22-31

[10] Yudong Zhang, Lenan Wu, B Peterson, Zhengchao Dong. A Two-Level Iterative Reconstruction Method for Compressed Sensing MRI [J]. Journal of Electromagnetic Waves and Applications. 2011, 25(8/9): 1081-1091

[11] Yudong Zhang, Lenan Wu, N Neggaz, Shuihua Wang, Geng Wei. Remote-sensing Image Classification Based on an Improved Probabilistic Neural Network [J]. Sensors. 2009, 9(9): 7516-7539

[12] Yudong Zhang, Lenan Wu. Crop Classification by forward neural network with adaptive chaotic particle swarm optimization [J]. Sensors. 2011, 11(5): 4721-4743

[13] Yudong Zhang, Lenan Wu. Pattern recognition via PCNN and Tsallis entropy [J]. Sensors. 2008, 8(11):7518-7529

[14] Yudong Zhang, Lenan Wu. Classification of Fruits using Computer Vision and a Multi-class Support Vector Machine [J], Sensors, 2012, 12(9): 12489-12505

[15] Yudong Zhang, Bradley Peterson, Zhengchao Dong, A Support-Based Reconstruction for SENSE MRI [J]. Sensors, 2013, 13(4): 4029-4040

[16] Yudong Zhang, Lenan Wu, Geng Wei, Shuihua Wang. A novel algorithm for all pairs shortest path problem based on matrix multiplication and pulse coupled neural network [J]. Digital Signal Processing. 2011, 21(4): 517-521

[17] Yudong Zhang, Lenan Wu. Stock Market Prediction of S&P 500 via combination of improved BCO Approach and BP Neural Network [J]. Expert systems with applications. 2009, 36(5): 8849-8854

[18] Yudong Zhang, Zhengchao Dong, Lenan Wu, Shuihua Wang. A hybrid method for MRI brain image classification [J]. Expert Systems with Applications. 2011, 38(8): 10049-10053

[19] Yudong Zhang, Jun Yan, Geng Wei, Lenan Wu. Find Multi-Objective Paths in Stochastic Networks via Chaotic Immune PSO [J]. Expert Systems with Applications. 2010, 37(3): 1911-1919