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Selected Peer-Reviewed Publications
Communication-Optimal Distributed Dynamic Graph Clustering ,
Chunjiang Zhu, Tan Zhu, Kam-Yiu Lam, Song Han, and Jinbo Bi
To appear in the Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion ,
Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, and Bowen Zhou
To appear in the Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
Top-down Indoor Localization with Wi-Fi Fingerprints using Deep Q-network ,
Fei Dou, Jin Lu, Zigeng Wang, Xia Xiao, Jinbo Bi, Chun-Hsi Huang
To appear in the Proceedings of the 15th IEEE International Conference on Mobile Ad-hoc and Sensor Systems, 2018.
Large-scale Automatic Depression Screening Using Meta-data from Wi-Fi Infrastructure ,
Shweta Ware, Chaoqun Yue, Reynaldo Morillo, Jin Lu, Chao Shang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Athanasios Bamis, and Bing Wang
Proceedings of the ACM on Interactive Mobile, Wearable and Ubiquitous Technologies (IMWUT), a premier journal for research relevant to the post-PC era, 2(4):195, pp.195:1-195:27, 2018.
Fusion Location Data for Depression Prediction ,
Chaoqun Yue, Shweta Ware, Reynaldo Morillo, Jin Lu, Chao Shang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Athanasios Bamis, and Bing Wang
IEEE Transactions on Big Data, DOI: 10.1109/TBDATA.2018.2872569, 2018.
Inferring Phenotypes from Substance Use via Collaborative Matrix Completion ,
Jin Lu, Jiangwen Sun, Xinyu Wang, Henry R. Kranzler, Joel Gelernter, and Jinbo Bi
BMC Systems Biology, 12(S6):104, DOI: 10.1186/s12918-018-0623-5, 2018.
Reforming Generative Autoencoders via Goodness-of-Fit Hypothesis Testing ,
Aaron Palmer, Dipak K. Dey, and Jinbo Bi
Proceedings of the Uncertainty in Artificial Intelligence (UAI), 2018.
Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning ,
Jin Lu, Chao Shang, Chaoqun Yue, Reynaldo Morillo, Shweta Ware, Jayesh Kamath, Athanasios Bamis, Alexander Russell, Bing Wang, and Jinbo Bi
Proceedings of the ACM on Interactive Mobile, Wearable and Ubiquitous Technologies (IMWUT), a premier journal for research relevant to the post-PC era, 2(1):21, pp.21:1-21:21, 2018.
Latent Sparse Modeling of Longitudinal Multi-dimensional Data ,
Ko-Shin Chen, Tingyang Xu, and Jinbo Bi
Proceedings of the 32nd AAAI Conference on Artificial Intelligence, pp. 2135-2142, 2017.
Collaborative Phenotype Inference from Comorbid Substance Use Disorders and Genotypes ,
Jin Lu, Jiangwen Sun, Xinyu Wang, Henry R. Kranzler, Joel Gelernter, and Jinbo Bi
Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 392-397, 2017.
VIGAN: Missing View Imputation with Generative Adversaial Networks ,
Chao Shang, Aaron Palmer, Jiangwen Sun, Ko-Shin Chen, Jin Lu, and Jinbo Bi
Proceedings of IEEE International Conference on Big Data (BigData), 2017.
Identifying and Quantifying Nonlinear Structured Relationships in Complex Manufactural Systems ,
Tingyang Xu, Tan Yan, Dongjin Song, Wei Cheng, Haifeng Chen, Guofei Jiang, and Jinbo Bi
Proceedings of IEEE International Conference on Big Data (BigData), 2017.
Fusing Location Data for Depression Prediction ,
Chaoqun Yue, Shweta Ware, Reynaldo Morillo, Jin Lu, Chao Shang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Anthanasios Bamis, and Bing Wang
Proceedings of the 14th International Conference on Ubiquitous Intelligence and Computing (UIC), 2017.
Classification of Neurological Gait Disorders Using Multi-task Feature Learning ,
Ioannis Papavasileiou, Wenlong Zhang, Xin Wang, Jinbo Bi, Li Zhang, Song Han
Proceedings of the 2nd IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), 2017.
A Sparse Inductive Model for Matrix Completion with Side Information ,
Jin Lu, Guannan Liang, Jiangwen Sun, and Jinbo Bi
Advances in Neural Information Processing Systems 29, pp. 4071 – 4079, 2016.
A supplementary file with proofs can be found here . A more efficient proof will be published in a journal version.
Behavior vs. Introspection: Refining Prediction of Clinical Depression via Smartphone Sensing Data ,
Asma Ahmad Farhan, Chaoqun Yue, Reynaldo Morillo, Shweta Ware, Jin Lu, Jinbo Bi, Jayesh Kamath, Alexander Russell, Athanasios Bamis, and Bing Wang
Proceedings of IEEE Wireless Health Conference, 2016.
A Cross-species Bi-clustering Approach to Identifying Conserved Co-regulated Genes ,
Jiangwen Sun, Zhongliang Jiang, Xiuchun Tian, and Jinbo Bi
Bioinformatics, 32(12):137-146, PMID: 27307610, PMCID: PMC4908362; DOI: 10.1093/bioinformatics/btw278, 2016.
Bi-convex Optimization to Learn Classifiers from Multiple Biomedical Annotations ,
Xin Wang and Jinbo Bi
IEEE/ACM Transactions on Computaitonal Biology and Bioinformatics, PMID: 27295686 DOI: 10.1109/TCBB.2016.2576457, pp. 1-13, 2016.
Multi-view Bi-clustering to Identify Smartphone Sensing Features Indicative of Depression ,
Asma Ahmad Farhan, Jin Lu, Jinbo Bi, Alexander Russell, Bing Wang, and Athanasios Bamis
Proceedings of IEEE International Conference on Connected Health: Application, Systems and Engineering Technologies (CHASE), pp.264–273, 2016.
Machine Learning Identification of EEG Features Predicting Working Memory Performance in Schizophrenia and Healthy Adults ,
Jason Johannesen, Jinbo Bi, Ruhua Jiang, Joshua Kenney and Chi-Ming Chen
BMC Neuropsychiatric Electrophysiology, 2:3 DOI: 10.1186/s40810-016-0017-0, 2016.
Quantifying Feed Efficiency of Dairy Cattle for Genome-wide Association Analysis ,
Tingyang Xu, Jiangwen Sun, Erin E Connor, and Jinbo Bi
Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp.131-134, 2015.
An Effective Method to Identify Heritable Components from Multivariate Phenotypes ,
Jiangwen Sun, Henry R. Kranzler, and Jinbo Bi
PLoS ONE 10(12):e0144418. doi:10.1371/journal.pone.0144418, 2015. The related software package is in github .
Multiplicative Multi-Task Feature Learning ,
Xin Wang, Jinbo Bi, Shipeng Yu, Jiangwen Sun, and Minghu Song
Accepted by the Journal of Machine Learning Research, 2015.
Refining Multivariate Disease Phenotypes for High Chip Heritability ,
Jiangwen Sun, Henry R. Kranzler, and Jinbo Bi
BMC Medical Genomics, 8(Suppl 3):S3, DOI:10.1186/1755-8794-8-S3-S3, pp. 1-14, 2015. The related software package is here .Announcement: A lot of typeset/edit errors were created in the production process of BMC Medical Genomics that affect the scientific content of this paper. Hence, we suggest readers to ignore the online version from the journal website.
Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction ,
Tingyang Xu, Jiangwen Sun, and Jinbo Bi
Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), pp. 1345-1354, 2015.
Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization ,
Jiangwen Sun, Jin Lu, Tingyang Xu, and Jinbo Bi
Proceedings of the 32nd International Conference on Machine Learning (ICML), pp. 757-766, 2015.
Spatio-temporal Modeling of EEG Data for Understanding Working Memory ,
Jinbo Bi, Tingyang Xu, Chi-Ming Chen, and Jason Johannesen
Peer reviewed and archived by ICML Workshop on Statistics, Machine Learning and Neuroscience , 2015.
Learning Classifiers from Dual Annotation Ambiguity via a Min-Max Framework ,
Jinbo Biand Xin Wang
Neurocomputing, 151(2):891-904, 2015.
Detecting Tympanostomy Tubes from Otoscopic Images via Offline and Online Training ,
Xin Wang, Tulio A Valdez, and Jinbo Bi
Computers in Biology and Medicine, 61:107-118, 2015.
On Multiplicative Multi-Task Feature Learning ,
Xin Wang, Jinbo Bi, Shipeng Yu, and Jiangwen Sun
Advances in Neural Information Processing Systems (NIPS), pp. 2411-2419, 2014.
Identifying Heritable Composite Traits from Multivariate Phenotypes with Genome-wide SNPs ,
Jiangwen Sun, Jinbo Biand Henry R. Kranzler
Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 340-344, 2014.
A Sparse Integrative Cluster Analysis for Understanding Soybean Phenotypes ,
Jinbo Bi, Jiangwen Sun, Tingyang Xu, Jin Lu, Yansong Ma, and Lijuan Qiu
Workshop Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp.1-7, 2014. Won the best paper award out of 200 workshop papers in 17 workshops.
A Viewpoint of Security for Digital Health Care: What’s There? What Works? What’s Needed? ,
Steve Demurjian, Alberto De la Rosa Algarin, Jinbo Bi, Soloman Berhe, Thomas Agresta, Xiaoyan Wang, Michael Blechner
International Journal of Privacy and Health Information Management, 2(1):1-21, 2014.
Transcriptional Profiles of Bovine In Vivo Pre-implantation Development ,
Zongliang Jiang, Jiangwen Sun, Hong Dong, Oscar Luo, Xinbao Zheng, Craig Obergfell, Yong Tang, Jinbo Bi, Rachel O’Neill, Yijun Ruan, Jingbo Chen, and Xiuchun (Cindy) Tian
BMC Genomics, 15:756-770, 2014. (Identified as a “highly accessed” article by the journal.)
Translating Effective Paper-based Disease Management into Electronic Medical Systems ,
Tingyang Xu, Michelle M Cloutier, and Jinbo Bi
Proceedings of the 2nd IEEE International Conference on Health Informatics (ICHI), pp. 101-108, 2014.
Multi-view Singular Value Decomposition for Disease Subtyping and Genetic Associations ,
Jiangwen Sun, Jinbo Bi, and Henry R. Kranzler
BMC Genetics, 15(73):1-12, 2014. (Identified as a “highly accessed” article by the journal.) The related software package is here .
Multi-view Biclustering for Genotype-Phenotype Association Studies of Complex Diseases ,
Jiangwen Sun, Jinbo Biand Henry R. Kranzler
Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 316-321, 2013.
Quadratic Optimization to Identify Highly Heritable Quantitative Traits from Complex Phenotypic Features ,
Jiangwen Sun, Jinbo Biand Henry R. Kranzler
Proceedings of ACM Special Interest Group on Knowledge Discovery from Data Mining (SIGKDD), pp. 811-819, 2013.
Comparing the Utility of Homogeneous Subtypes of Cocaine Use and Related Behaviors with DSM-IV Cocaine Dependence as Traits for Association Analysis ,
Jinbo Bi, Joel Gelernter, Jiangwen Sun and Henry R. Kranzler
American Journal of Medical Genetics (Part B) Neuropsychiatric Genetics (AJMG), 165B(2):148-156, 2014.
Dopamine D1 Receptor Gene Variation Modulates Opioid Dependence Risk by Affecting Transition to Addiction ,
Feng Zhu, Chunxia Yan, Yi-chong Wen, Jiayin Wang, Jinbo Bi, Ya-ling Zhao, Yang Zhao, Lai Wei, Yu-cheng Guo, Jing Wang, Yan Zhao, Chengge Gao, Wei Jia and Shengbin Li
PLoS ONE, 8(8):e70805-1-11, 2013.
Multiview Comodeling to Improve Genetic Association of Complex Disease Phenotypes ,
Jiangwen Sun, Jinbo Biand Henry R. Kranzler
IEEE Journal of Biomedical and Health Informatics, 18(2):548-554, 2014.
A Machine Learning Approach to College Drinking Prediction and Risk Factor Identification ,
Jinbo Bi, Jiangwen Sun, Yu Wu, Howard Tennen, Stephen Armeli
ACM Transactions on Intelligent Systems and Technology, 4(4):72:1-24, 2013.
Efficient Techniques for Genotype-Phenotype Correlational Analysis ,
Subrata Saha, Sanguthevar Rajasekaran, Jinbo Biand Sudipta Pathak
BMC Medical Informatics and Decision Making, 13(1):41-59, 2013.
A Multi-Objective Program for Quantitative Subtyping of Clinically Relevant Phenotypes ,
Jiangwen Sun, Jinbo Biand Henry R. Kranzler
Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM2012), pp.256-261, 2012.
Improved Methods to Identify Stable, Highly Heritable Subtypes of Opioid Use and Related Behaviors ,
Jiangwen Sun, Jinbo Bi, Grace Chan, David Oslin, Lindsay Farrer, Joel Gelernter, Henry R. Kranzler
Addictive Behaviors, 37(10):1138-1144, 2012.
1-Norm Support Vector Machine for College Drinking Risk Factor Identification ,
Michael Zuba, Joseph Gilbert, Yu Wu, Jinbo Bi, Howard Tennen and Stephen Armeli
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, pp. 651-660, Jan. 2012.
An Intelligent Web-based Decision Support Tool for Enhancing Asthma Guideline Adherence ,
Jinbo Biand Arun Abraham
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, pp. 51-59, Jan. 2012.
Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach ,
Meizhu Liu, Le Lu, Jinbo Bi, Vikas Raykar, Matthias Wolf and Marcos Salganicoff
Proceedings of the 14th International Conference on Medical Image Computing and Computer Assisted Intervention, 2011.
AdaBoost on Low-Rank PSD Matrices for Metric Learning ,
Jinbo Bi, Dijia Wu, Le Lu, Meizhu Liu, Yimo Tao and Matthias Wolf
Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR2011), 2011.
Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images ,
Le Lu, Jinbo Bi, Matthias Wolf and Marcos Salganicoff
Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR2011), 2011.
Matrix-Variate and Higher-Order Probabilistic Projections ,
Shipeng Yu, Jinbo Bi and Jieping Ye,
Data Mining and Knowledge Discovery, 22(3):372-392, 2011.
Correcting Misalignment of Automatic 3D Detection by Classification: Ileo-cecal Valve False Positive Reduction in CT Colonography ,
Le Lu, Matthias Wolf, Jinbo Bi, and Marcos Salganicoff,
Proceedings of the 13th International Conference on Medical Image Computing and Computer Assisted Intervention. Joint with Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging, 2010.
Stratified Learning of Local Anatomical Context for Lung Nodules in CT Images ,
Dijia Wu, Le Lu, Jinbo Bi, Yoshihisa Shinagawa, Kim Boyer, Arun Krishnan, Marcos Salganicoff,
Proceedings of the 13th IEEE International Conference on Computer Vision and Pattern Recognition (CVPR2010), 2010.
Hierarchical Learning for Tubular Structure Parsing in Medical Imaging: A Study on Coronary Arteries Using 3D CT Angiography ,
Le Lu, Jinbo Bi, Shipeng Yu, Zhigang Peng, Arun Krishnan and Xiang Zhou,
Proceedings of the IEEE International Conference on Computer Vision (ICCV’09), 2009.
A Two-Level Approach Towards Semantic Colon Segmentation: Removing Extra-colonic Findings ,
Le Lu, Matthais Wolf, Jianming Liang, Murat Dundar, Jinbo Bi and Marcos Salganicoff,
Proceedings of Annual Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI’09), 2009.
A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis ,
Dijia Wu, Jinbo Bi and Kim Boyer,
Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’09), 2009.
An Improved Multi-task Learning Approach with Applications in Medical Diagnosis ,
Jinbo Bi, Tao Xiong, Shipeng Yu, Murat Dundar, Bharat Rao,
Proceedings of the 18th European Conference on Machine Learning (ECML’08), 2008.
Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer ,
Vikas Raykar, Balaji Krishnapuram, Jinbo Bi, Murat Dundar, Bharat Rao,
Proceedings of the 25th International Conference on Machine Learning (ICML’08), 2008.
Local Characteristic Features for Computer Aided Detection of Pulmonary Embolism in CT Angiography ,
Jianming Liang and Jinbo Bi,
Proceedings of Pulmonary Image Analysis at Annual Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’08-PIA), 2008.
Stratified Regularity Measures with Jensen-Shannon Divergence ,
Kazunori Okada, Senthil Periaswamy and Jinbo Bi,
Proceedings of the IEEE International Computer Vision and Pattern Recognition Workshops, 2008.
Large Scale Diagnostic Code Classification for Medical Patient Records ,
Lucian Vlad Lita, Shipeng Yu, Stefan Niculescu and Jinbo Bi,
Proceedings of the 3rd International Joint Conference on Natural Language Processing (IJCNLP’08), 2008.
Automatic Medical Coding of Patient Records via Weighted Ridge Regression ,
Jianwu Xu, Shipeng Yu, Jinbo Bi, Lucian Vlad Lita, Stefan Niculescu and Bharat Rao,
Proceedings of the 6th International Conference on Machine Learning and Applications (ICMLA’07), 2007.
LungCAD: A Clinically Approved, Machine Learning System for Lung Cancer Detection ,
R Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salganicoff, Nancy Obuchowski and David Naidich,
Proceedings of the 13th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD’07), 2007.
A Mathematical Programming Formulation for Sparse Collaborative Computer Aided Diagnosis ,
Jinbo Bi and Tao Xiong,
Proceedings of the 22nd International Conference on Artificial Intelligence (AAAI’07), 2007.
Joint Optimization of Cascaded Classifiers for Computer Aided Detection ,
Murat Dundar and Jinbo Bi,
Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’07), 2007.
Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure ,
Jinbo Bi and Jianming Liang,
Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’07), 2007.
This paper focuses on the classification approaches used in Siemens research project of pulmonary embolism detection.
Computer Aided Detection of Pulmonary Embolism with Tobogganing and Multiple Instance Classification in CT Pulmonary Angiography ,
Jianming Liang and Jinbo Bi,
Proceedings of the 20th International Conference on Information Processing in Medical Imaging (IPMI’07), 2007.
This paper focuses on the initial identification of suspicious regions for Siemens research project of pulmonary embolism detection.
Robust Parametric Modeling Approach Based on Domain Knowledge for Computer Aided Detection of Vertebrae Column Metastases in MRI ,
Anna Jerebko, G.P. Schmidt, Xiang Zhou, Jinbo Bi, V. Anand, J. Liu, S. Schoenberg, I. Schmueching, B. Kiefer and A. Krishnan,
Proceedings of the 20th International Conference on Information Processing in Medical Imaging (IPMI’07), 2007.
Automated Heart Abnormality Detection Using Sparse Linear Classifiers ,
Maleeha Qazi, Glenn Fung, Sriram Krishnan, Jinbo Bi, Bharat Rao and Alan Katz,
IEEE Engineering Magazine in Medicine and Biology, 26(2):56-63, March/April 2007.
An early version appeared in Special session on “Application of Machine Learning in Medicine and Biology” of The 4th International Conference on Machine Learning and Applications (ICMLA), 2005.
On the Medical Frontier: the 2006 KDD Cup Competition ,
Terran Lane, Bharat Rao, Jinbo Bi, Jianming Liang, Marcos Salganicoff,
ACM Journal SIGKDD Explorations, 8(2):39-46, Dec 2006.
Probabilistic Joint Feature Selection for Multi-task Learning ,
Tao Xiong, Jinbo Bi, Bharat Rao and Vladimir Cherkassky
Proceedings of SIAM International Conference on Data Mining (SDM’06), 2006.
Learning Classifiers When the Training Data is not IID ,
Murat Dundar, Balaji Krishnapuram, Jinbo Bi and Bharat Rao,
Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI’06), 2006.
Efficient Model Selection for Regularized Linear Discriminant Analysis ,
Jieping Ye, Tao Xiong, Qi Li, Ravi Janardan, Jinbo Bi, Vladimir Cherkassky and Chandra Kambhamettu,
Proceedings of the ACM Fifteenth Conference on Information and Knowledge Management (CIKM’06), 2006.
Automatic View Recognition for Cardiac Ultrasound Images ,
Matthew E. Otey, Jinbo Bi, Sriram Krishnan, Bharat Rao, Jonathan Stoeckel, Alan Katz, Jing Han and Srinivasan Parthasarathy,
Proceedings of the 1st International Workshop on Computer Vision for Intravascular and Intracardiac Imaging at Annual Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’06-CVII), 2006.
Computer Aided Detection via Asymmetric Cascade of Sparse Hyperplane Classifiers ,
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Toshiro Kubota, Glenn Fung, Marcos Salganicoff and Bharat Rao,
Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD’06), 2006.
MILES: Multiple-Instance Learning via Embedded Instance Selection ,
Yixin Chen, Jinbo Bi, James Z. Wang,
IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(12):1-17, 2006.
Active Learning via Transductive Experimental Design ,
Kai Yu, Jinbo Bi, Volker Tresp,
Proceedings of the 23rd International Conference on Machine Learning (ICML’06), 2006.
Semi-supervised Mixture of Kernels via LPBoost Methods ,
Jinbo Bi, Glenn Fung, Murat Dundar, and Bharat Rao,
Proceedings of the 15th IEEE International Conference on Data Mining (ICDM’05), 2005.
A Sparse Support Vector Machine Approach to Region-based Image Categorization ,
Jinbo Bi, Yixin Chen and James Wang,
Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), 2005.
Sparse Fisher Discriminant Analysis for Computer Aided Detection ,
Murat Dundar, Glenn Fung, Jinbo Bi, S. Sandilya and Bharat Rao,
Proceedings of SIAM International Conference on Data Mining (SDM’05), 2005.
Clustering by Maximizing Sum-of-squared Separation Distance ,
Yixin Chen and Jinbo Bi,
Proceedings of SIAM Data Mining Workshop on Clustering High Dimensional Data and its Applications, 2005.
Support Vector Classification with Input Data Uncertainty ,
Jinbo Bi and Tong Zhang,
Advances in Neural Information Processing Systems (NIPS’04), vol. 17, pp 161-168, 2004.
Column-Generation Boosting Methods for Mixture of Kernels ,
Jinbo Bi, Tong Zhang and Kristin Bennett,
Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’04), pp. 521-526, 2004.
A Fast Iterative Algorithm for Fisher Discriminant using Heterogeneous Kernels ,
Glenn Fung, Murat Dundar, Jinbo Bi and Bharat Rao,
Proceedings of the 21st International Conference on Machine Learning (ICML’04), 2004.
Regression Error Characteristic Curves ,
Jinbo Bi and Kristin Bennett,
Proceedings of the 20th International Conference on Machine Learning (ICML’03), 2003.
Multi-Objective Programming in SVMs ,
Jinbo Bi,
Proceedings of the 20th International Conference on Machine Learning (ICML’03), 2003.
Learning with Rigorous Support Vector Machines ,
Jinbo Bi and Vladimir Vapnik,
Proceedings of the 16th Annual Conference on Learning Theory (COLT’03), 2003.
A Geometric Approach to Support Vector Regression ,
Jinbo Bi and Kristin Bennett,
Neurocomputing, 55(1-2):79-108, 2003.
Dimensionality Reduction via Sparse Support Vector Machines ,
Jinbo Bi, Kristin Bennett, Mark Embrechts, Curt Breneman and Minghu Song,
Journal of Machine Learning Research, 3:1229-1243, 2003.
Prediction of Protein Retention Times in Anion-exchange Chromatography Systems Using Support Vector Machines ,
M. Song, C. Breneman, Jinbo Bi, N. Sukumar, K. Bennett, S. Cramer and N. Tugcu,
Journal of Chemical Information and Computer Science. 42(6):1347-1357, 2003.
Descriptor Generation, Selection and Model Building in Quantitative Structure-Property Analysis,
C. Breneman, K. Bennett, M. Embrechts, S. Cramer, M. Song and Jinbo Bi,
A book chapter in Experimental Design for Combinatorial and High Throughput Materials Development, J Crawse Ed. 2002.
Duality, Geometry, and Support Vector Regression ,
Jinbo Bi and Kristin Bennett,
Advances in Neural Information Processing Systems (NIPS’01), 2001.
Calibrating the Adaptive Learning Rate to Improve Convergence of ADAM ,
Qianqian Tong, Guannan Liang and Jinbo Bi
– unpublished manuscript
Stochastic Privacy-Preserving Methods for Nonconvex Sparse Learning ,
Guannan Liang, Qianqian Tong, Jiahao Ding, Miao Pan and Jinbo Bi
– unpublished manuscript
Perceived Stress, Self-Efficiency, and the Cerebral Morphometric Markers in Binge-drinking Young Adults ,
Guangfei, Li, Thang M. Le, Wuyi Wang, Simon Zhornitsky, Yu Chen, Shefali Chaudhary, Tan Zhu, Sheng Zhang, Jinbo Bi, Xiaoying Tang and Chiang-Shan R. Li,
– unpublished manuscript
An Efficient Tensor Regression with Latent Sparse Regularization ,
Guannan Liang, Ko-Shin Chen, Tingyang Xu, Jun Yan, Minghu Song and Jinbo Bi
– unpublished manuscript
Machine Learning Analysis of Aggregated Cocaine Treatment Studies to Understand the Efficacy of Modafinil ,
Tan Zhu, Daniel Ruskin, Kyle M. Kampman and Jinbo Bi
– unpublished manuscript