J. Bi

发表

Active learning via transductive experimental design

Jinbo Bi, Volker Tresp, Kai Yu, 2006, ICML.

Prediction of Protein Retention Times in Anion-Exchange Chromatography Systems Using Support Vector Regression

Jinbo Bi, Kristin P. Bennett, Steven M. Cramer, 2002, J. Chem. Inf. Comput. Sci..

MILES: Multiple-Instance Learning via Embedded Instance Selection

Yixin Chen, James Ze Wang, Jinbo Bi, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Support Vector Classification with Input Data Uncertainty

Jinbo Bi, Tong Zhang, Tong Zhang, 2004, NIPS.

Classification of Neurological Gait Disorders Using Multi-task Feature Learning

Wenlong Zhang, Masayoshi Tomizuka, Jinbo Bi, 2016, 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

Column-generation boosting methods for mixture of kernels

Jinbo Bi, Tong Zhang, Kristin P. Bennett, 2004, KDD.

L G ] 3 A pr 2 01 8 1 A Survey on MultiView Clustering

J. Bi, Shiliang Sun, Guoqing Chao, 2018 .

Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data pdf

Jinbo Bi, Guannan Liang, Qianqian Tong, 2020, ArXiv.

Probabilistic Interpretations and Extensions for a Family of 2D PCA-style Algorithms

Jieping Ye, J. Bi, Shipeng Yu, 2008 .

Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and Challenges

Umar Farooq Ghumman, J. Bi, Zhiqiang Shen, 2020, Polymers.

Predicting depressive symptoms using smartphone data

J. Bi, Athanasios Bamis, B. Wang, 2020 .

Automatic View Recognition for Cardiac Ultrasound Images

J. Bi, M. Otey, Jonathan Stoeckel, 2006 .

Multi-view singular value decomposition for disease subtyping and genetic associations

J. Bi, H. Kranzler, Jiangwen Sun, 2014, BMC Genetics.

A genome-wide association study of cocaine use disorder accounting for phenotypic heterogeneity and gene–environment interaction

J. Bi, J. Gelernter, H. Kranzler, 2019, Canadian journal of surgery. Journal canadien de chirurgie.

A min-max framework of cascaded classifier with multiple instance learning for computer aided diagnosis

Kim L. Boyer, Jinbo Bi, Dijia Wu, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

Clustering by Maximizing Sum-of-Squared Separation Distance

J. Bi, Yixin Chen, 2005 .

Genome-wide Association Analysis

J. Bi, Tingyang Xu, Jiangwen Sun, 2015 .

Reduction of lymph tissue false positives in pulmonary embolism detection

J. Bi, M. Salganicoff, Bernard Ghanem, 2008, SPIE Medical Imaging.

Spatio-Temporal Modeling of EEG Data for Understanding Working Memory

J. Bi, Chi-Ming A. Chen, Tingyang Xu, 2015 .

Identifying alcohol misuse biotypes from neural connectivity markers and concurrent genetic associations

J. Bi, C. Lejuez, Yu Chen, 2022, Translational Psychiatry.

Cognitive Challenges Are Better in Distinguishing Binge From Nonbinge Drinkers: An Exploratory Deep‐Learning Study of fMRI Data of Multiple Behavioral Tasks and Resting State

J. Bi, C. Li, Wuyi Wang, 2022, Journal of magnetic resonance imaging : JMRI.

Effect of three-dimensional porosity gradients of biomimetic coatings on their bonding strength and cell behavior.

J. Bi, Changmin Hu, Tomas Silva Santisteban, 2020, Journal of biomedical materials research. Part A.

2 Medical Background Knowledge 2 . 1 What is Coronary Artery Disease ?

R. B. Rao, Glenn Fung, J. Bi, 2006 .

A Survey on Multi-View Clustering

J. Bi, Shiliang Sun, Guoqing Chao, 2022 .

Auto-Encoding Goodness of Fit

Zhiyi Chi, J. Bi, Derek Aguiar, 2022, ICLR.

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining

J. Bi, Tong Geng, Caiwen Ding, 2022, DAC.

Heterogeneous Graph Sparsification for Efficient Representation Learning

J. Bi, Chandan Chunduru, Chunjiang Zhu, 2022, ArXiv.

Machine Learning Analysis of Aggregated Cocaine Treatment Studies to Understand the Efficacy of Modafinil

J. Bi, K. Kampman, D. Ruskin, 2021 .

GaitCode: Gait-based continuous authentication using multimodal learning and wearable sensors

Jinbo Bi, Wenlong Zhang, Zhi Qiao, 2020 .

Discrete Graph Structure Learning for Forecasting Multiple Time Series

J. Bi, Jie Chen, Chao Shang, 2021, ICLR.

Large Scale Diagnostic Code Classification for Medical Patient Records

Jinbo Bi, Lucian Vlad Lita, Shipeng Yu, 2008, IJCNLP.

An Improved Multi-task Learning Approach with Applications in Medical Diagnosis

Murat Dundar, Jinbo Bi, R. Bharat Rao, 2008, ECML/PKDD.

Learning with Rigorous Support Vector Machines

Jinbo Bi, Vladimir Vapnik, V. Vapnik, 2003, COLT.

Dimensionality Reduction via Sparse Support Vector Machines

Jinbo Bi, Kristin P. Bennett, Mark J. Embrechts, 2003, J. Mach. Learn. Res..

Accelerating Large-Scale Molecular Similarity Search through Exploiting High Performance Computing

Jinbo Bi, Tan Zhu, Chun Jiang Zhu, 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A Sparse Interactive Model for Matrix Completion with Side Information

Jinbo Bi, Jin Lu, Jiangwen Sun, 2016, NIPS.

Transcriptional profiles of bovine in vivo pre-implantation development

Craig Obergfell, Jinbo Bi, Jiangwen Sun, 2014, BMC Genomics.

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion pdf

Bowen Zhou, Chao Shang, Jinbo Bi, 2018, AAAI.

Improved methods to identify stable, highly heritable subtypes of opioid use and related behaviors.

Jinbo Bi, Jiangwen Sun, David Oslin, 2012, Addictive behaviors.

An Effective Method to Identify Heritable Components from Multivariate Phenotypes

Jinbo Bi, Jiangwen Sun, J. Bi, 2015, PloS one.

Dopamine D1 Receptor Gene Variation Modulates Opioid Dependence Risk by Affecting Transition to Addiction

J. Bi, Chun-xia Yan, Jiayin Wang, 2013, PloS one.

Machine learning identification of EEG features predicting working memory performance in schizophrenia and healthy adults

Jinbo Bi, Ruhua Jiang, Jason K. Johannesen, 2016, Neuropsychiatric electrophysiology.

Refining multivariate disease phenotypes for high chip heritability

J. Bi, H. Kranzler, Jiangwen Sun, 2015, BMC Medical Genomics.

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization

Jinbo Bi, Jin Lu, Jiangwen Sun, 2015, ICML.

Efficient techniques for genotype‐phenotype correlational analysis

Sanguthevar Rajasekaran, Jinbo Bi, Subrata Saha, 2013, BMC Medical Informatics and Decision Making.

OctSurf: Efficient hierarchical voxel-based molecular surface representation for protein-ligand affinity prediction.

Blake Blumenfeld Gaines, J. Bi, Minghu Song, 2021, Journal of molecular graphics & modelling.

Detecting tympanostomy tubes from otoscopic images via offline and online training

Jinbo Bi, Tulio A. Valdez, Xin Wang, 2015, Comput. Biol. Medicine.

Robust Parametric Modeling Approach Based on Domain Knowledge for Computer Aided Detection of Vertebrae Column Metastases in MRI

Jinbo Bi, V. Anand, J. Liu, 2007, IPMI.

Translating Effective Paper-Based Disease Management into Electronic Medical Systems

Jinbo Bi, Tingyang Xu, Michelle M. Cloutier, 2014, 2014 IEEE International Conference on Healthcare Informatics.

Comparing the utility of homogeneous subtypes of cocaine use and related behaviors with DSM‐IV cocaine dependence as traits for genetic association analysis

Jinbo Bi, Jiangwen Sun, Joel Gelernter, 2014, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

Duality, Geometry, and Support Vector Regression

Kristin P. Bennett, Jinbo Bi, J. Bi, 2001, NIPS.

A Survey on Multiview Clustering pdf

Shiliang Sun, Jinbo Bi, Guoqing Chao, 2017, IEEE Transactions on Artificial Intelligence.

Benchmark on Indexing Algorithms for Accelerating Molecular Similarity Search

Jinbo Bi, Chun Jiang Zhu, Minghu Song, 2020, J. Chem. Inf. Model..

On Multiplicative Multitask Feature Learning

Jinbo Bi, Xin Wang, Shipeng Yu, 2014, NIPS.

Multiview Comodeling to Improve Subtyping and Genetic Association of Complex Diseases

Jinbo Bi, Jiangwen Sun, Henry R. Kranzler, 2014, IEEE Journal of Biomedical and Health Informatics.

A multi-objective program for quantitative subtyping of clinically relevant phenotypes

Jinbo Bi, Jiangwen Sun, Henry R. Kranzler, 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine.

Escaping Saddle Points with Stochastically Controlled Stochastic Gradient Methods pdf

Guannan Liang, Qianqian Tong, Chunjiang Zhu, 2021, ArXiv.

Learning Classifiers When the Training Data Is Not IID

Murat Dundar, Jinbo Bi, R. Bharat Rao, 2007, IJCAI.

Convolutional neural network for automated mass segmentation in mammography

Jinbo Bi, Reda Ammar, Sheida Nabavi, 2018, BMC Bioinformatics.

Alcohol Expectancy and Cerebral Responses to Cue-Elicited Craving in Adult Nondependent Drinkers.

Thang M. Le, Shenmin Zhang, J. Bi, 2019, Biological psychiatry. Cognitive neuroscience and neuroimaging.

Against Membership Inference Attack: Pruning is All You Need

Hang Liu, Sanguthevar Rajasekaran, Jinbo Bi, 2020, IJCAI.

Residual Deep Learning System for Mass Segmentation and Classification in Mammography

Jinbo Bi, Reda Ammar, Sheida Nabavi, 2019, BCB.

Multi-view cluster analysis with incomplete data to understand treatment effects

Jinbo Bi, Jin Lu, Jiangwen Sun, 2019, Inf. Sci..

Bayesian multiple instance learning: automatic feature selection and inductive transfer

Murat Dundar, Jinbo Bi, R. Bharat Rao, 2008, ICML '08.

Federated Nonconvex Sparse Learning pdf

Jinbo Bi, Tan Zhu, Qianqian Tong, 2020, ArXiv.

Multi-view spectral graph convolution with consistent edge attention for molecular modeling

Chao Shang, Jinbo Bi, Minghu Song, 2021, Neurocomputing.

Local Characteristic Features for Computer Aided Detection of Pulmonary Embolism in CT Angiography

Jinbo Bi, Jianming Liang, J. Bi, 2008 .

Computer Aided Detection of Pulmonary Embolism with Tobogganing and Mutiple Instance Classification in CT Pulmonary Angiography

Jinbo Bi, Jianming Liang, J. Bi, 2007, IPMI.

Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure

Jinbo Bi, Jianming Liang, J. Bi, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

An Effective Tensor Regression with Latent Sparse Regularization

J. Bi, Minghu Song, Tingyang Xu, 2022, Journal of Data Science.

A sparse support vector machine approach to region-based image categorization

Yixin Chen, James Ze Wang, Jinbo Bi, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

Perceived stress, self-efficacy, and the cerebral morphometric markers in binge-drinking young adults

Thang M. Le, Shenmin Zhang, J. Bi, 2021, NeuroImage: Clinical.

Identifying and quantifying nonlinear structured relationships in complex manufactural systems

Wei Cheng, Jinbo Bi, Haifeng Chen, 2017, 2017 IEEE International Conference on Big Data (Big Data).

Effective 3D object detection and regression using probabilistic segmentation features in CT images

Jinbo Bi, Le Lu, Marcos Salganicoff, 2011, CVPR 2011.

Stochastic privacy-preserving methods for nonconvex sparse learning

J. Bi, Jiahao Ding, Qianqian Tong, 2022, Inf. Sci..

An Effective Hard Thresholding Method Based on Stochastic Variance Reduction for Nonconvex Sparse Learning

Jinbo Bi, Chun Jiang Zhu, Qianqian Tong, 2020, AAAI.

Edge Attention-based Multi-Relational Graph Convolutional Networks pdf

Jinfeng Yi, Chao Shang, Jinbo Bi, 2018, ArXiv.

Stratified learning of local anatomical context for lung nodules in CT images

Kim L. Boyer, Jinbo Bi, Le Lu, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper)

Hang Liu, Jinbo Bi, Hongwu Peng, 2021, 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning

Alexander Russell, Chao Shang, Jinbo Bi, 2018, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data

Alexander Russell, Jinbo Bi, Asma Ahmad Farhan, 2016, 2016 IEEE Wireless Health (WH).

Grant Report on SCH: Personalized Depression Treatment Supported by Mobile Sensor Analytics

Bing Wang, Alexander Russell, Jayesh Kamath, 2020, Journal of psychiatry and brain science.

Prediction of Protein Retention Times in Anion-Exchange Chromatography Systems Using Support Vector Regression.

Jinbo Bi, Kristin P. Bennett, Steven M. Cramer, 2003 .

Large-scale Automatic Depression Screening Using Meta-data from WiFi Infrastructure

Alexander Russell, Chao Shang, Jinbo Bi, 2018, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

1-norm support vector machine for college drinking risk factor identification

Michael Zuba, Jinbo Bi, Yu Wu, 2012, IHI '12.

Transcriptional profiles of bovine in vivo pre-implantation development

J. Bi, R. O’Neill, Y. Ruan, 2014, BMC Genomics.

A machine learning approach to college drinking prediction and risk factor identification

Jinbo Bi, Yu Wu, Jiangwen Sun, 2013, ACM Trans. Intell. Syst. Technol..

Mining Medical Images

Xiang Zhou, Murat Dundar, Jinbo Bi, 2009 .

Fusing Location Data for Depression Prediction

Alexander Russell, Chao Shang, Jinbo Bi, 2021, IEEE Transactions on Big Data.

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Jinbo Bi, Jiangwen Sun, Tingyang Xu, 2015, KDD.

Multi-view Bi-clustering to Identify Smartphone Sensing Features Indicative of Depression

Alexander Russell, Jinbo Bi, Asma Ahmad Farhan, 2016, 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

Deep statistical modelling of nanopore sequencing translocation times reveals latent non-B DNA structures

J. Bi, R. O’Neill, D. Aguiar, 2023, Bioinform..

Semi-supervised mixture of kernels via LPBoost methods

Murat Dundar, Jinbo Bi, Glenn Fung, 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

Calibrating the adaptive learning rate to improve convergence of ADAM

Jinbo Bi, Qianqian Tong, Guannan Liang, 2019, Neurocomputing.

Calibrating the Learning Rate for Adaptive Gradient Methods to Improve Generalization Performance pdf

Jinbo Bi, Qianqian Tong, Guannan Liang, 2019, ArXiv.

A Deep Molecular Generative Model Based on Multi-Resolution Graph Variational Autoencoders

Jinbo Bi, zhenxiang gao, xinyu wang, 2021 .

VIGAN: Missing view imputation with generative adversarial networks

Chao Shang, Aaron Palmer, Jinbo Bi, 2017, 2017 IEEE International Conference on Big Data (Big Data).

Sparse Fisher Discriminant Analysis for Computer Aided Detection

Murat Dundar, Jinbo Bi, Glenn Fung, 2005, SDM.

Customized Positional Encoding to Combine Static and Time-varying Data in Robust Representation Learning for Crop Yield Prediction

J. Bi, Meijian Yang, Qinqing Liu, 2023, IJCAI.

Machine Learning Crop Yield Models Based on Meteorological Features and Comparison with a Process-Based Model

J. Bi, Guiling Wang, Meijian Yang, 2022, Artificial Intelligence for the Earth Systems.

Regression Error Characteristic Curves

Jinbo Bi, Kristin P. Bennett, J. Bi, 2003, ICML.

Automatic depression screening using social interaction data on smartphones

J. Bi, Athanasios Bamis, Alexander Russell, 2022, Smart Health.

Asynchronous Parallel Stochastic Quasi-Newton Methods

Jinbo Bi, Chunjiang Zhu, Xingyu Cai, 2020, Parallel Comput..

Differentially Private and Communication Efficient Collaborative Learning

Miao Pan, Jinbo Bi, Guannan Liang, 2021, AAAI.

Fusing location data for depression prediction

Alexander Russell, Chao Shang, Jinbo Bi, 2017, 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

A Bisection Reinforcement Learning Approach to 3-D Indoor Localization

Jinbo Bi, Jin Lu, Tingyang Xu, 2021, IEEE Internet of Things Journal.

AdaBoost on low-rank PSD matrices for metric learning

Jinbo Bi, Le Lu, Dijia Wu, 2011, CVPR 2011.

Inferring phenotypes from substance use via collaborative matrix completion

Jinbo Bi, Jin Lu, Jiangwen Sun, 2018, BMC Systems Biology.

Collaborative phenotype inference from comorbid substance use disorders and genotypes

Jinbo Bi, Xinyu Wang, Jin Lu, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A fast iterative algorithm for fisher discriminant using heterogeneous kernels

Murat Dundar, Jinbo Bi, Glenn Fung, 2004, ICML.

A cross-species bi-clustering approach to identifying conserved co-regulated genes

Jinbo Bi, Jiangwen Sun, Zongliang Jiang, 2016, Bioinform..

Quadratic optimization to identify highly heritable quantitative traits from complex phenotypic features

Jinbo Bi, Jiangwen Sun, Henry R. Kranzler, 2013, KDD.

Quadratic Optimization to Identify Highly Heritable Quantitative Traits from Complex Disease Features

J. Bi, Jiangwen Sun, 2013 .

Latent Sparse Modeling of Longitudinal Multi-Dimensional Data

Jinbo Bi, Tingyang Xu, Ko-Shin Chen, 2018, AAAI.

Matrix-variate and higher-order probabilistic projections

Jieping Ye, Jinbo Bi, Shipeng Yu, 2011, Data Mining and Knowledge Discovery.

Alcohol Expectancy and Cerebral Responses to Cue-Elicited Craving in Adult Nondependent Drinkers.

Thang M. Le, Shenmin Zhang, J. Bi, 2019, Biological psychiatry. Cognitive neuroscience and neuroimaging.

A sparse integrative cluster analysis for understanding soybean phenotypes

Jinbo Bi, Yansong Ma, Jin Lu, 2014, 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Bi-convex Optimization to Learn Classifiers from Multiple Biomedical Annotations

J. Bi, Xin Wang, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Calibrating the adaptive learning rate to improve convergence of ADAM

J. Bi, Qianqian Tong, Guannan Liang, 2019, Neurocomputing.

A geometric approach to support vector regression

Jinbo Bi, Kristin P. Bennett, J. Bi, 2003, Neurocomputing.

A Two-Level Approach Towards Semantic Colon Segmentation: Removing Extra-Colonic Findings

Murat Dundar, Jinbo Bi, Le Lu, 2009, MICCAI.

Automated heart abnormality detection using sparse linear classifiers.

Jinbo Bi, Glenn Fung, Sriram Krishnan, 2007, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

On Multiplicative Multitask Feature Learning

J. Bi, Shipeng Yu, Xin Wang, 2014, NIPS.

A Survey on Multiview Clustering

J. Bi, Shiliang Sun, Guoqing Chao, 2017, IEEE Transactions on Artificial Intelligence.

Efficient model selection for regularized linear discriminant analysis

Jieping Ye, Jinbo Bi, Qi Li, 2006, CIKM '06.