Publications

Publications and Citations at DBLP and by Google Scholar .

(*Graduate Student, **Undergraduate Student)

2021
Contrastive Learning of Sentence Representations

*Hefei Qiu, Wei Ding, Ping Chen, International Conference on Natural Language Processing (ICON), December 16-19, 2021.

Mitigating Class-Boundary Label Uncertainty to Reduce Both Model Bias and Variance

Matthew Almeida, Yong Zhuang, Wei Ding, Scott E. Crouter, and Ping Chen, ACM Trans. Knowl. Discov. Data 15, 2, Article 27 (April 2021), 18 pages.

2020
Clustering Sparse Data With Feature Correlation With Application to Discover Subtypes in Cancer

Jipeng Qiang, Wei Ding, Marieke L. Kuijjer, John Quackenbush, Ping Chen, IEEE Access 8: 67775-67789, March 2020.

Multi-Source Causal Feature Selection

Kui Yu, Lin Liu, Jiuyong Li, Wei Ding, Thuc Duy Le, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 42(9), 2240-2256, September 2020.

A Novel Deep Learning Model by Stacking Conditional Restricted Boltzmann Machine and Deep Neural Network

*Tianyu Kang, Ping Chen, John Quackenbush and Wei Ding, ACM SIGKDD Virtual Conference, August 23-27, 2020.

Catalysis Clustering With GAN By Incorporating Domain Knowledge

*Olga Andreeva, Wei Li, Wei Ding, Marieke Kuijjer, John Quackenbush and Ping Chen, ACM SIGKDD Virtual Conference, August 23-27, 2020.

2019
His-GAN: A Histogram-based GAN Model to Improve Data Generation Quality

Wei Li, Wei Ding, Rajani Sadasivam, Xiaohui Cui, Ping Chen, Neural Networks, Volume 119, November 2019, Pages 31-45, https://doi.org/10.1016/j.neunet.2019.07.001

BAMB: A Balanced Markov Blanket Discovery Approach to Feature Selection

Zhaolong Lin, Kui Yu, Hao Wang, Lin Liu, Wei Ding, and Xindong Wu, ACM Transactions on Intelligent Systems and Technology (TIST), September, 2019.

Heterogeneous-Length Text Topic Modeling for Reader-Aware Multi-Document Summarization

Jipeng Qiang, Ping Chen, Wei Ding, Tong Wang, Fei Xie, and Xindong Wu, ACM Transactions on Knowledge Discovery from Data (TKDD), 13, 4, Article 42 (August 2019), 21 pages. DOI: https://doi.org/10.1145/3333030

2018
Domain Agnostic Online Semantic Segmentation for Multi-Dimensional Time Series

Shaghayegh Gharghabi*, Chin-Chia Michael Yeh*, Yifei Ding*, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn Keogh, Data Mining and Knowledge Discovery, September, 2018.

Clustering on Sparse Data in Non-Overlapping Feature Space with Applications to Cancer Subtyping

Tianyu Kang*, Kourosh Zarringhalam, Marieke Kuijjer, Ping Chen, John Quackenbush, and Wei Ding, The IEEE International Conference on Data Mining (IEEE ICDM), Singapore, November 17-20, 2018.

Time Series Snippets: A New Primitive for Time Series Data Mining

Shima Imani+, Frank Madrid+, Wei Ding, Scott Crouter, and Eamonn Keogh, The IEEE International Conference on Big Knowledge (IEEE ICBK), Singapore, November 17-18, 2018.

Galaxy: Towards Scalable and Interpretable Explanation on High-dimensional and Spatio-Temporal Correlated Climate Data

Yong Zhuang*, David L. Small, Xin Shu, Kui Yu, Shafiqul Islam, and Wei Ding, The IEEE International Conference on Big Knowledge (IEEE ICBK), Singapore, November 17-18, 2018.

TL-PC: An Interpretable Causal Relationship Networks on Older Adults Fall Influence Factors

Zihan Li*, Wei Ding, Kui Yu, Suzanne Leveille, and Ping Chen, The IEEE International Conference on Big Knowledge (IEEE ICBK), Singapore, November 17-18, 2018.

Cancer Sutbype Identification Using Somatic Mutation Data

Marieke Kuijjer, Joseph Paulson, Peter Salzman, Wei Ding, and John Quackenbush, British Journal of Cancer, May 2018.

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data

Tianyu Kang*, Wei Ding, Luoyan Zhang, Daniel Ziemek, Kourosh Zarringhalam, BMC Bioinformatics, January 2018.

A Semantic QA-Based Approach for Tex Summarization Evaluation

Ping Chen, Fei Wu*, Tong Wang, Wei Ding, The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Louisiana, Feb 2-7, 2018.

2017
Markov Blanket Feature Selection Using Representative Sets

Kui Yu, Xindong Wu, Wei Ding, Yang Mu, Hao Wang, IEEE Transactions on Neural Networks and Learning Systems, Volume: 28, Pages: 2775 - 2788, Issue: 99, November 2017.

Learning Weighted Distance Metric from Group Level Information and Its Parallel Implementation

Hamidreza Mohebbi*, Wei Ding, Yang Mu, Applied Intelligence, 10.1007/s10489-016-0826-7, Volume 46, Issue 1, pp 180-196, January, 2017.

Crime Hot Spot Forecasting: A Recurrent model with Spatial and Temporal Information

Yong Zhuang*, Matthew Almeida*, Melissa Morabito, Wei Ding, IEEE International Conference on Big Knowledge, August 9 -10, 2017, Heifei, China.

2016
Activity recognition and intensity estimation in youth from accelerometer data aided by machine learning

Xiang Ren*, Wei Ding, Scott E. Crouter, Yang Mu, Rong Xie, Applied Intelligence,

Scalable and Accurate Online Feature Selection for Big Data

Kui Yu, Xindong Wu, Wei Ding, Jian Pei, ACM Transactions on Knowledge Discovery from Data (TKDD), 2016, Volume: 11 Issue: 2, Pages: 16:1-16:39, December 2016.

LOFS: A library of online streaming feature selection

Kui Yu, Wei Ding, Xindong Wu, Knowledge-Based Systems, Volume 113, Pages 1-3, December, 2016.

Common-Factor Approach for Multivariate Data Cleaning with an Application to Mars Phoenix Mission Data

Dongping Fang, Elizabeth Oberlin+, Wei Ding, and Samuel Kounaves, In JSM Proceedings, Physical and Engineering Sciences Section. Alexandria, VA: American Statistical Association. 1937-1950, August 2016.

Online Learning from Trapezoidal Data Streams

Qin Zhang+, Peng Zhang, Guodong Long, Wei Ding, Chengqi Zhang, Xindong Wu, IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume: 28 Issue: 9, On page(s): 2709-2723, Print ISSN: 1041-4347, Online ISSN: 1041-4347, Digital Object Identifier: 10.1109/TKDE.2016.2563424, October 2016.

Rapid Building Detection using Machine Learning

Joseph Paul Cohen*, Wei Ding, Caitlin Kuhlman, Aijun Chen, and Liping Di, Applied Intelligence, 45(2): 443-457, September 2016.

Hierarchical Spatio-Temporal Pattern Discovery and Predictive Modeling

Chung-Hsien Yu*, Wei Ding, Melissa Morabito, Ping Chen, IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(4): 979-993, April 2016.

Multi-document summarization using Closed Patterns

Ji-Peng Qiang+, Ping Chen, Wei Ding, Fei Xie, Xingdong Wu, Knowledge-Based Systems, 99: 28-38, May 2016.

Sacrificing Overall Classification Quality to Improve Classification Accuracy of Well-Sought Classes

Kevin M. Amaral*, Ping Chen, Wei Ding, Rajani Sadasivam, IEEE International Conference on Data Mining, PhD Forum, Dec 12-15, 2016, Barcelona, Spain.

Long-Lead Prediction of Extreme Precipitation Cluster Via a Spatio-Temporal Convolutional Neural Network

Yong Zhuang*, Wei Ding, 6th International Workshop on Climate Informatics, Boulder, CO, Sept 22-23, 2016.

Improving cognitive load level measurement through preprocessing of psychophysical Data by random subspace time-Series method

Nada Attar+, Paul Fomenky+, Wei Ding, Marc Pomplun, IEEE 2nd International Conference on Human Computer Interactions (ICHCI'16), pp. 1-6, IEEE, March, 2016.

A Comprehensive Literature Review on Big Data in Healthcare

Jingwei Li+, Wei Ding, Hsing Cheng, Ping Chen, Dehai Di, Wei Huang, AMCIS 22nd America’s Conference on Information Systems, San Diego, August 11-14, 2016.

Online Streaming Feature Selection on Long-lead Heavy Precipitation Forecasting

Yong Zhuang*, Kui Yu, Dawei Wang*, Wei Ding, the 13th IEEE International Conference on Networking, Sensing and Control (ICNSC'2016), Mexico City, Mexico on April 28-30, 2016.

RandomOut: Using a convolutional gradient norm to win The Filter Lottery

Joseph Paul Cohen*, Henry Lo*, Wei Ding, International Conference on Learning Representations (ICLR), Workshop Track, May 2-4, San Juan, Puerto Rico, 2016.

Scale Normalization

Henry Z. Lo*, Kevin Amaral*, Wei Ding, International Conference on Learning Representations (ICLR), Workshop Track, May 2-4, San Juan, Puerto Rico, 2016.

Proceedings of the 6th International Workshop on Climate Informatics: CI 2016 Intelligence, 45(2): 443-457, September 2016

A. Banerjee, W. Ding, J. Dy, V. Lyubchich, A. Rhines (Eds.), I. Ebert-Uphoff, C. Monteleoni, D. Nychka (Series Eds.), NCAR Technical Note NCAR/TN-529+PROC, Sept 2016, 159 pp., doi: 10.5065/D6K072N6.

2015
Classification with Streaming Features: An Emerging Pattern Mining Approach

Kui Yu, Wei Ding, Dan A. Simovici, Hao Wang, Jian Pei, and Xindong Wu, ACM Transactions on Knowledge Discovery from Data (TKDD), 2015, in press.

Convolutional Gradients for Feature Extraction and Analysis from Deep Neural Networks

Henry Lo*, Joseph Cohen*, Wei Ding, 11th IEEE International Conference on Automatic Face and Gesture Recognition, May 4-8, 2015, Ljubljana, Slovenia.

Proposing a New Friend Recommendation Method, FRUTAL, to Enhance Social Media Providers' Performance

Zhou Zhang+, Yuewen Liu, Wei Ding, Wei (Wayne) Huang, Qin Su, Ping Chen, Decision Support Systems (DSS), Elsevier, accepted, July 20, 2015.

A Hierarchical Framework for Learning Climate Science Data and Forecasting Extreme Weather Events

Dawei Wang and Wei Ding, IEEE International Conference on Data Mining (IEEE ICDM), November 14-17, 2015, Atlantic City, NJ, USA.

Tornado Forecasting with Multiple Markov Boundaries

Kui Yu, Dawei Wang*, Wei Ding, Jian Pei, David Small, Shafiqul Islam, Xindong Wu, 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 10-13, 2015, Sydney, Australia.

Towards Mining Trapezoidal Data Streams

Qin Zhang+, Peng Zhang , Guodong Long , Wei Ding, Chengqi Zhang , and Xindong Wu, IEEE International Conference on oData Mining (IEEE ICDM), November 14-17, 2015, Atlantic City, NJ, USAICDM.

Understanding Deep Networks with Gradients

Henry Lo*, Wei Ding, IEEE International Conference on Data Mining (IEEE ICDM) PhD Forum, November 14, 2015, Atlantic City, NJ, USA.

Convolutional Gradients for Feature Extraction and Analysis from Deep Neural Networks

Henry Lo*, Joseph Cohen*, Wei Ding,11th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 4-8, 2015, Ljubljana, Slovenia.

Monitoring Sleep and Detecting Irregular Nights through Unconstrained Smartphone Sensing

Ke Huang+, Xiang Ding, Jing Xu, Guanling Chen, Wei Ding, the 12th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2015), August 10-14, 2015, in Beijing, China.

Teleconnection Signals Effect on Terrestrial Precipitation: Big Data Analytics vs. Wavelet Analysis CI2015poster

Yahui Di, Wei Ding, Sanaz Imen, Ni-Bin Chang, The 5th International Workshop on Climate Informatics, Septebmer 24-25, 2015 (poster), Boulder, CO, USA.

Spatio-Temporal Asynchronous Co-Occurrence Pattern for Big Climate Data towards Long-Lead Flood Prediction

Chung-Hsien Yu, Dong Luo, Wei Ding, Joseph Cohen, David Small, and Shafiqul Islam, the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Oct 29 – Nov 01, 2015, Santa Clara, CA, USA

One-Day Activities for K-12 Face-to-Face Outreach

D. Garcia, W. Ding, J. Cohen*, B. Ericson, J. Gray, D. Reed, panel on ACM Special Interest Group on Computer Science Education (SIGCSE), March, 2015, Kansas City, MI.

A Friend Recommendation System Using Users' Information of Total Attribute

Zhou Zhang+, Yuewen Liu, Wei Ding, Wei Wayne Huang, Data Science, Springer International Publishing Switzerland, 2015.

Apply Machine Learning to Long-Lead Heavy Precipitation Prediction

Yahui Di*, Wei Ding, Nibin Chang, David Small, Shafiqul Islam, 12th IEEE International Conference on Networking, Sensing and Control, April 9-11, 2015, Taipei, Taiwan.

A Common Factor Approach for Multivariate Data Cleaning with an Application to Mars Phoenix Mission Data

D. Fang, W. Ding, E. Oberlin, S. Kounaves, the Joint Statistical Meetings (JSM 2015), Seattle, August 8-13, WA.

Computational Reanalysis of the Phoenix Lander Wet Chemistry Lab Data

E. Oberlin, F. Dong, W. Ding, S. Kounaves, The 46th Lunar and Planetary Science Conference, the Woodlands, TX, March, 2015

2014
Face Recognition from Multiple Images per Subject

Yang Mu*, Henry Lo*, Wei Ding, and Dacheng Tao, ACM International Conference on Multimedia (ACM MM), Orlando, Florida, November, 2014.

Towards Scalable and Accurate Online Feature Selection for Big Data

Kui Yu, Xindong Wu, Wei Ding, and Jian Pei, IEEE International Conference on Data Mining (IEEE ICDM), Shenzhen, China, December, 2014.

Authorship identification from unstructured texts

C. Zhang+, X. Wu, Z. Niu, W. Ding, Knowledge-Based Systtem. 66: 99-111 (2014) .

Temporality and Context for Detecting Adverse Drug Reactions from Longitudinal Data

Henry Lo*, Wei Ding, Zohreh Nazeri, Applied Intelligence, in press, 2014.

Local Learning on High Dimension, Imbalanced, and Noisy Data: A Framework for Long-Lead Extreme Precipitation Clusters Forecasting

D. Wang*, W. Ding, Y. Mu, D. Small, S. Islam, The Fourth Workshop on Understanding Climate Change through Data, June, 2014, Boulder, CO.

Crime Forecasting Using Spatio-Temporal Pattern with Ensemble Learning

C. Yu*, W. Ding, P. Chen, M. Morabito, Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), May, 2014, Tainan, Taiwan.

Bipart: Learning Block Structure for Activity Detection

Y. Mu*, H. Lo*, W. Ding, K. Amaral**, S. E. Crouter, IEEE Transactions on Knowledge and Data Engineering (TKDE), in press, 2014.

Mining Sequential Patterns with Periodic Wildcard Gaps

Y. Wu, L. Wang, J. Ren, W. Ding, X. Wu, Applied Intelligence, in press, 2014.

Mars and Beyond: Human Spaceflight at the Museum of Science Boston

J. P. Cohen*, W. Ding, J. Sable, R. Li, T. Stepinski, The 45th Lunar and Planetary Science Conference, the Woodlands, TX, March, 2014.

Gaussian Noise Removal for Wet Chemistry Data from the Phoenix Mission

Y. Mu*, W. Ding, X. Ren, E. Oberlin, S. Kounaves, The 45th Lunar and Planetary Science Conference, the Woodlands, TX, March, 2014.

Data Mining with Big Data

X. Wu, X. Zu, G. Wu, W. Ding, IEEE Transactions on Knowledge and Data Engineering (TKDE), 97-107, January, 2014.

2013
Markov Blanket Feature Selection with Non-Faithful Data Distributions

K. Yu, X. Wu, Z. Zhang, Y. Mu, H. Wang, W. Ding, IEEE International Conference on Data Mining (ICDM), Dallas, TX, USA, December, 2013.

Group Feature Selection with Streaming Features

H. Li+, X. Wu, Z. Li, W. Ding, IEEE International Conference on Data Mining (ICDM), Dallas, TX, USA, December, 2013.

Local Discriminative Distance Metrics and Their Real World Applications

Y. Mu*, W. Ding, Ph.D. Forum in conjunction with IEEE International Conference on Data Mining (ICDM), Dallas, TX, USA, December, 2013.

Mining Adverse Drug Reactions from Electronic Health Records

H. Lo*, W. Ding, Z. Nazeri, Ph.D. Forum in conjunction with IEEE International Conference on Data Mining (ICDM), Dallas, TX, USA, December, 2013.

Crater Detection via Genetic Search Methods to Reduce Image Features

J. Cohen*, W. Ding, Advances in Space Research, 2013. (Joseph Cohen received the Outstanding Paper Award for Young Scientists from the Committee on Space Research of the International Council for Science)

Constrained Stochastic Gradient Descent for Large-scale Least Squares Problem

Y. Mu*, W. Ding, T. Zhou, D. Tao, the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Chicago, USA, August, 2013.

Towards Long-Lead Forecasting of Extreme Flood Events: a Data Mining Framework for Precipitation Cluster Precursors Identification

D. Wang*, W. Ding, K. Yu, X. Wu, P. Chen, D. Small, S. Islam, the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Chicago, USA, August, 2013.

Online Group Feature Selection from Feature Streams

H. Li*, X. Wu, W. Ding, the 20th AAAI Conference on Artificial Intelligence (AAAI-13), Bellevue, WA, July, 2013.

Discriminative Accelerometer Patterns in Children Physical Activities

Y. Mu*, H. Lo*, K. Amaral**, W. Ding, S. E. Crouter, the 3rd International Conference on Ambulatory Monitoring of Physical Activity and Movement, Amherst, MA, June, 2013

Two-Tiered Machine Learning Model for Estimating Energy Expenditure in Children

K. Amaral**, Y. Mu*, H. Lo*, W. Ding, S. E. Crouter, the 3rd International Conference on Ambulatory Monitoring of Physical Activity and Movement, Amherst, MA, June, 2013

PNFS: Personalized Web News Filtering and Summarization

X. Wu, F. Xie*, G. Wu, and W. Ding, International Journal on Artificial Intelligence Tools, 2013.

Understanding the Spatial Distribution of Crime Based on Its Related Variables Using Geospatial Discriminative Pattern

D. Wang*, W. Ding, H. Lo, M. Morabito, P. Chen, J. Salazar, and T. Stepinski, Computers, Environment and Urban Systems, Elsevier, 2013

To Introduce Computer Science in One Day, The Throw Platform

J. P. Cohen*, W. Ding, D. Boisvert, the 3rd IEEE Integrated STEM Education Conference (ISEC), Princeton, NJ, March, 2013

Local Discriminative Distance Metrics Ensemble Learning

Y. Mu*, W. Ding, D. Tao, The Journal of the Pattern Recognition Society, Elsevier, 2013

Feature Selection by Joint Graph Sparse Coding

X. Zhu*, X. Wu, W. Ding, S. Zhang, SIAM International Conference on Data Mining (SDM), Austin, Texas, USA, May, 2013

2012
Crime Hotspot Mapping Using the Crime Related Factors--A Spatial Data Mining Approach

D. Wang*, W. Ding, H. Lo, T. Stepinski, J. Salazar, and M. Morabito, Applied Intelligence, Springer, 2012

Self-Taught Active Learning from Crowds

M. Fang*, X. Zhu, B. Li, W. Ding, X. Wu, the IEEE International Conference on Data Mining (ICDM), Belgium, December, 2012

Bridging Causal Relevance and Pattern Discriminability: Mining Emerging Patterns from High-Dimensional Data

K. Yu*, W. Ding, H. Wang, and X. Wu, IEEE Transactions on Knowledge and Data Engineering, 2012

Online Feature Selection with Streaming Features

X. Wu, K. Yu*, W. Ding, H. Wang, and X. Zhu, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012.

Geospatial Contrast Mining with Applications on Labeled Spatial Data

W. Ding, T. F. Stepinski, Josue Salazar*, Contrast Data Mining: Concepts, Algorithms and Applications, Editors: Guozhu Dong and James Bailey, ISBN-13: 978-1439854327, Chapman & Hall/CRC, Data Mining and Knowledge Discovery Series, September, 2012.

Modern Advances in intelligent Systems And Tools

W. Ding, H. Jiang, M. Ali, M. Li (Eds.), Studies in Computational Intelligence 431, Springer, ISBN 978-3-642-30731-7, 2012.

Advanced Research in Applied Artificial Intelligence

H. Jiang, W. Ding, M. Ali, X. Wu (Eds.), Proceedings of 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, LANI 7345, Springer, Dalian, China, ISBN 978-3642310867, June 2012.

Coupled Behavior Analysis for Capturing Coupling Relationships in Group-based Market Manipulations

Y. Song*, L. Cao, X. Wu, G. Wei, W. Ye, W. Ding, the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, to appear, Beijing, China, August, 2012

Mining Emerging Patterns by Streaming Feature Selection

K. Yu*, W. Ding, D. A. Simovici, X. Wu, the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, to appear, Beijing, China, August, 2012

Cyber-Physical Integration to Connect Vehicles for Transformed Transportation Safety and Efficiency

D. Ni, H. Liu, W. Ding, Y. Xie, H. Wang, H. Pishro-Nik, and Q. Yu, The 25th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, pp. 78-87, June, Dalian, China, 2012

Adaptive Selective Learning for Automatic Identification of Sub-Kilometer Craters

S. Liu*, W. Ding, F. Gao, T. Stepinski, Neurocomputing, 2012

Exploring Causal Relationships with Streaming Features

K. Yu*, X. Wu, W. Ding, H. Wang, in press, The Computer Journal, in press, 2012.

Several Remarks on Mining Frequent Trajectories in Graphs

H. Z. Lo*, D. A. Simovici, and W. Ding, The 25th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, June, Dalian, China, 2012

Optimization of Criminal HotSpots Based on Underlying Crime Controlling Factors Using Geospatial Discriminative Pattern

D. Wang*, W. Ding, T. Stepinski, J. Salazar*, and M. Morabito, The 25th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, June, Dalian, China, 2012

Virtual Lab of Connected Vehicle Technology

D. Ni, H. Liu, Y. Xie, W. Ding, H. Wang, H. Pishro-Nik, Q. Yu, M. Ferreira*, 2012 Spring Simulation Multiconference, March, 2012

MarsWeekend: A Panel and Games at the Museum of Science Boston

J. P. Cohen*, W. Ding, J. Sable, R. Li, T. Stepinski, The 43rd Lunar and Planetary Science Conference, the Woodlands, TX, March, 2012

2011
Crime Forecasting Using Data Mining Techniques

C. Yu*, M. Ward*, M. Morabito, and W. Ding, The 4th Workshop on Data Mining Case Studies and Practice Prize, Vancouver, Canada, December, 2011

Causal Associative Classification

K. Yu*, X. Wu, W. Ding, and H. Wang, the 2011 IEEE International Conference on Data Mining (ICDM), Vancouver, CA, December, 2011.

Bernoulli Trials Based Feature Selection for Crater Detection

S. Liu*, W. Ding, J. P. Cohen*, D. Simovici, T. Stepinski, the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Chicago, IL, November, 2011

Personalized News Filtering and Summarization on the Web

X. Wu, F. Xie*, G. Wu, W. Ding, the 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Boca Raton, FL, November, 2011 (Best Paper Award) .

Detection of Sub-Kilometer Craters in High Resolution Planetary Images Using Shape and Texture Features

L. Bandeira*, W. Ding, T.F. Stepinski, Advances in Space Research (2011), doi: 10.1016/j.asr.2011.08.021

Empirical Discriminative Tensor Analysis for Crime Forecasting

Y. Mu*, W. Ding, M. Morabito, D. Tao, the 5th International Conference on Knolwege Science, Engineering and Management, Irvine, CA, December, 2011

Genetically Enhanced Feature Selection of Discriminative Planetary Crater Image Features

J. P. Cohen*, S. Liu*, W. Ding, the 24th Australasian Joint Conference on Artificial Intelligence, Perth, Australia, December, 2011

Machine Learning Approaches to Detecting Impact Craters in Planetary Images

T. F. Stepinski, W. Ding, R. Vilalta, Intelligent Data Analysis for Real-Life Applications: Theory and Practice, IGI Global, 2011

Regional Association Rule Mining and Scoping from Spatial Data

W. Ding, C. F. Eick, Data Mining: Foundations and Intelligent Paradigms, Editor: Lakhmi Jain, Springer Verlag's -Smart Innovation, Systems and Technologies Book Series, 2011

Semi-Supervised Active Class Selection for Automatic Identification of Sub-Kilometer Craters

S. Liu*, W. Ding, T. Stepinski, 7th International Symposium on Image and Signal Processing and Analysis (ISPA 2011), Dubrovnik, Croatia, September, 2011

Crater Detection Using Bayesian Classifiers and LASSO

Y. Wang*, W. Ding, K. Yu*, H. Wang, X. Wu, IEEE International Conference on Intelligent Computing and Integrated Systems, Guilin, Guangxi, China, October, 2011

Biologically Inspired Model for Crater Detection

Y. Mu*, W. Ding, D. Tao, T.F. Stepinski, International Joint Conference on Neural Networks(IJCNN), San Jose, CA, August, 2011

Adaptive Study Design through Semantic Association Rule Analysis

P. Chen, W. Ding, W. Garcia**, International Journal of Software Science and Computational Intelligence (IJSSCI), in press, 2011

Entropy Quad-Trees for High Complexity Regions Detection

R. Vetro*, D. A. Simovici, W. Ding, International Journal of Software Science and Computational Intelligence (IJSSCI), in press, 2011

Cascading Crater Detection with Active Learning

W. I. Mille*r, T. F. Stepinski, Y. Mu*, W. Ding, in Proc. of 42nd Lunar and Planetary Science Conference, the Woodlands, TX, March, 2011

Feasibility Study For Automatic Calibration Of Transportation Simulation Models

H, Liu, Q. Yu, W. Ding, H. Wang, S. Shannon*, in Proc. of the Simulation Multiconference (SpringSim), Boston, MA, April, 2011

Sub-Kilometer Crater Discovery with Boosting and Transfer Learning Pre-Print(in color):

W. Ding, T. Stepinski, Y. Mu*, L. Bandeira*, R. Vilalta, Y. Wu*, Z. Lu*, T. Cao*, X. Wu, ACM Transactions on Intelligent Systems and Technology, 2011

Word Sense Disambiguation with Automatically Acquired Knowledge

P. Chen, W. Ding, M. Choly**, C. Bowes**, the international journal of IEEE Intelligent Systems, 2011

2010
Causal Discovery from Streaming Features

K. Yu*, X. Wu, H. Wang, W.Ding, in Proc. of the IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia, December, 2010.

Using Model Checking to Generate Test Cases for Critical Systems

W. Ding, LAP Lambert Academic Publishing, Germany, ISBN: 978-3-8433-5565-0, 2010

Exploring Labeled Spatial Datasets Using Association Analysis (Demo Paper)

T. Stepinski, J. Salazar**, W. Ding, in Proc. of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2010), San Jose, California, November, 2010

Automatic Detection of Craters in Planetary Images: An Embedded Framework Using Feature Selection and Boosting

W. Ding, T. Stepinski, L. Bandeira*, R. Vilalta, Y. Wu*, Z. Lu*, T. Cao*, in Proc. of the 19th ACM International Conference on Information and Knowledge Management (CIKM 2010), Toronto, Canada, October, 2010

ESTATE: Strategy for Exploring Labeled Spatial Datasets Using Association Analysis

T. Stepinski, J. Salazar**, W. Ding, D. White, in Proc. of the 13th International Conference on Discovery Science (DS10), Canberra, Australia, October, 2010.

One-Class Learning and Concept Summarization for Vaguely Labeled Data Streams

X. Zhu, W. Ding, P. Yu, C. Zhang, the international journal of Knowledge and Information Systems (KAIS), 2010.

A Framework for Regional Association Rule Mining and Scoping in Spatial Datasets

W. Ding, C. Eick, X. Yuan, J. Wang*, J. Nicot, the international journal of GeoInformatica, 2010.

TreeMatch: A Fully Unsupervised WSD System Using Dependency Knowledge on a Specific Domain

A. Tran**, C. Bowes**, D. Brown**, P. Chen, M. Choly**, W. Ding, in Proc. of the SemEval 2010 Workshop with the 48th Annual Meeting of the Association for Computational Linguistics (ACL), July, 2010. Uppsala, Sweden.

Online Streaming Feature Selection

X. Wu, K. Yu*, H. Wang, W. Ding, in Proc. of the 27th International Conference on Machine Learning (ICML 2010), Haifa, Israel, June, 2010.

Mining for High Complexity Regions Using Entropy and Box Counting Dimension Quad-Trees

R. Vetro, W. Ding and D. Simovici, in Proc. of the 9th IEEE International Conference on Cognitive Informatics, Beijing, China, July, 2010.(Best Paper Award)

Discovering Spatio-Social Motifs of Electoral Support Using Discriminative Pattern Mining

T. Stepinski, J. Salazar**, W. Ding, Com.Geo, in Proc. of the 1st International Conference on Computing for Geospatial Research and Application, Washington, DC, June, 2010.

Effective Classification for Crater Detection: A Case Study on Mars

J. Wang*, W. Ding, B. Fradkin*, C. H. Pham*, P. Sherman*, B. D. Tran*, D. Wang*, Y. Yang* and T. F. Stepinski, in Proc. of the 9th IEEE International Conference on Cognitive Informatics, Beijing, China, July, 2010.

Controlling Patterns of Geospatial Phenomena

T. Stepinski, W. Ding, C. Eick, the international journal of GeoInformatica, DOI: 10.1007/s10707-010-0107-2, 2010.

2009
Large-scale Dependency Knowledge Acquisition and its Extrinsic Evaluation through Word Sense Disambiguation

P. Chen, W. Ding, D. Brown**, C. Bowes**, in Proc. of the international Conference on Tools with Artificial Intelligence (ICTAI 2009), New Jersey, USA, November, 2009

A Fully Unsupervised Word Sense Disambiguation Method and Its Evaluation on Coarse-grained All-words Task

P. Chen, W. Ding, C. Bowes**, D. Brown**, in Proc. of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT 2009), Boulder, Colorado, May 2009

A Gaze-Controlled Interface to Virtual Reality Applications for Motor- and Speech-Impaired Users

W. Ding, P. Chen, H. Al-Mubaid, M. Pomplun, in Proc. of the HCI International 2009, San Diego, CA, July 2009.

A Lexical Knowledge Representation Model for Natural Language Understanding

P. Chen, W. Ding, C. Ding, the International Journal of Cognitive Informatics and Natural Intelligence (IJCiNi), 2009.

Word Classification: An Experimental Approach with Naive Bayes

W. Ding, H. Al-Mubaid, S. Kotagiri*, in Proc. of the ISCA 24th International Conference on Computers and Their Applications (CATA-2009), New Orleans, Louisiana, April, 2009

Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets

W. Ding, T. Stepinski, J. Salazar**, in Proc. of the SIAM International Conference on Data Mining (SDM), Nevada, April 2009.

Discovery of Feature-Based Hot Spots Using Supervised Clustering

W. Ding, T.Stepinski, R. Parmar*, D. Jiang*, C. F. Eick, in the International Journal of Computers and Geosciences, Elsevier, March 2009.

2008
Parsing Tree Matching Based Question Answering

P. Chen, W. Ding, T. Simmons**, C. Lacayo**, in Proc. of the Text Analysis Conference (TAC) Workshop, Gaithersburg, Maryland USA, November, 2008.

Discovering Controlling Factors of Geospatial Variables

T.F. Stepinski, W. Ding and C.F. Eick, in Proc. of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2008), Irvine, CA, USA, November, 2008.(Best Poster Presentation Award)

Finding Regional Co-Location Patterns for Sets of Continuous Variables

C. F. Eick, R. Parmar*, W. Ding, T. F. Stepinski, J. P. Nicot, in Proc. of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2008), Irvine, CA, USA, November, 2008.

Towards Regional Knowledge Discovery in Spatial Datasets

W. Ding, R. Jiamthapthaksin, R.Parmar*, D. Jiang*, T. F. Stepinski, and C. F. Eick, in Proc. of the Pacific-Asia Conf. on Knowledge Discovery and Data Mining, Osaka, Japan, May, 2008.

An Interactive Visualization Model for Large High-Dimensional Datasets

W. Ding, Ping Chen, the international journal of Data Engineering: Mining, Information, and Intelligence. Editors: Yupo Chan, John Talburt, Terry Talley, Springer, 2008.

2007 and earlier
On Regional Association Rule Scoping

W. Ding and C. Eick and X. Yuan and J. Wang* and J.P. Nicot, in Proc. of the International workshop on Spatial and Spatio-temporal Data Mining in Cooperation with IEEE ICDM 2007, Omaha, NE, USA, October, 2007

Mining Regional Knowledge in Spatial Datasets

W. Ding, C. Eick, in Proc. of the Grace Hopper Celebration of Women in Computing, Orlando, FL, October 2007.

A Framework for Regional Association Rule Mining in Spatial Datasets

W. Ding and C. Eick and J. Wang* and X. Yuan, in Proc. of the 6th IEEE International Conference on Data Mining (IEEE-ICDM'06), Hong Kong, China, December, 2006.

SenseNet: A Knowledge Representation Model for Computational Semantics

P. Chen, W. Ding, C. Ding, in Proc. of the 5th IEEE International Conference on Cognitive Informatics, Beijing, China, July, 2006.

Parametric Surface Denoising

I.A. Kakadiaris, I. Konstantinidis, E. Papadakis, W. Ding, D.J. Kouri, and D.K. Hoffman, in Proc. of the SPIE Wavelets XI, E. Papadakis, A. Laine, M. Unser (Eds), San Diego, CA, USA, July, 2005.

Web-based Interactive Visualization of Data Cubes

X. Wang, P. Chen, and W. Ding, in Proc. of the 2005 International Conference on Modeling, Simulation and Visualization Methods (MSV'05), Las Vegas, USA, June, 2005.

Using a Pre-Assessment Exam to Construct an Effective Concept-based Genetic Program for Predicting Course Success

G. Boetticher, W. Ding, C. Moen, and K. Yue, in Proc. of the 36th SIGCSE Technical Symposium on Computer Science Education (ACM SIGCSE'05), pp. 500-504, St. Louis, Missouri, USA, Feb. 2005.

Design and Evolution of an Undergraduate Course on Web Application Development

K. Yue, W. Ding, in Proc. of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ACM ITiCSE'04), pp. 22-26, Leeds, UK, June, 2004

A Model for Open Content Communities to Support Effective Learning and Teaching

K. Yue, A. Yang, W. Ding, and P. Chen, in Proc. of the IADIS International Conference on Web-based Communities, pp. 533-536, Lisbon, Portugal, April 2004.

Knowledge Management for Agent-based Tutoring Systems

P. Chen, W. Ding, Designing Distributed Learning Environments: With Intelligent Software Agents, pp. 146-161, Ed. F. Lin, Idea Group, Inc., 2004.

Open Courseware and Computer Science Education

K. Yue, A. Yang, W. Ding, and P. Chen, the ACM Journal of Computing Sciences in Colleges, Volume 20, Issue 1, Utah, USA, October, 2004.

Icon-based Visualization of Large High-Dimensional Datasets

P. Chen, C. Hu, W. Ding, and H. Lynn, in Proc. of the 3rd IEEE International Conference on Data Mining (ICDM'03), pp. 505-508, Melbourne, Florida, Nov. 2003.

Using a Model Checker to Test Safety Properties

P. Ammann, W. Ding, and D. Xu*, in Proc. of the 7th IEEE International Conference on Engineering of Complex Computer Systems, pp. 212-221, Skovde, Sweden, June 2001.

Evaluation of Three Specification-based Testing Criteria

A. Abdurazik, P. Ammann, W. Ding, and J. Offutt, in Proc. of the 6th IEEE International Conference on Engineering of Complex Computer Systems, pp. 179-187, Tokyo, Japan, Sept. 2000.

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