Duality, Geometry, and Support Vector Regression. - Jinbo Bi; Kristin P. Bennett (NIPS, 2001)

Prediction of Protein Retention Times in Anion-Exchange Chromatography Systems Using Support Vector Regression. - Minghu Song; Curt M. Breneman; Jinbo Bi; Nagamani Sukumar; Kristin P. Bennett; Steven M. Cramer; Nihal Tugcu (J. Chem. Inf. Comput. Sci., 2002)

Learning with Rigorous Support Vector Machines. - Jinbo Bi; Vladimir Vapnik (COLT, 2003)

Multi-Objective Programming in SVMs. - Jinbo Bi (ICML, 2003)

Regression Error Characteristic Curves. - Jinbo Bi; Kristin P. Bennett (ICML, 2003)

A geometric approach to support vector regression. - Jinbo Bi; Kristin P. Bennett (Neurocomputing, 2003)

Dimensionality Reduction via Sparse Support Vector Machines. - Jinbo Bi; Kristin P. Bennett; Mark J. Embrechts; Curt M. Breneman; Minghu Song (J. Mach. Learn. Res., 2003)

A fast iterative algorithm for fisher discriminant using heterogeneous kernels. - Glenn Fung; Murat Dundar; Jinbo Bi; R. Bharat Rao (ICML, 2004)

Column-generation boosting methods for mixture of kernels. - Jinbo Bi; Tong Zhang 001; Kristin P. Bennett (KDD, 2004)

Support Vector Classification with Input Data Uncertainty. - Jinbo Bi; Tong Zhang 001 (NIPS, 2004)

A Sparse Support Vector Machine Approach to Region-Based Image Categorization. - Jinbo Bi; Yixin Chen 002; James Ze Wang (CVPR (1), 2005)

Semi-Supervised Mixture of Kernels via LPBoost Methods. - Jinbo Bi; Glenn Fung; Murat Dundar; R. Bharat Rao (ICDM, 2005)

Sparse classifiers for Automated HeartWall Motion Abnormality Detection. - Glenn Fung; Maleeha Qazi; Sriram Krishnan; Jinbo Bi; R. Bharat Rao; A. Katz (ICMLA, 2005)

Sparse Fisher Discriminant Analysis for Computer Aided Detection. - Murat Dundar; Glenn Fung; Jinbo Bi; Sathyakama Sandilya; R. Bharat Rao (SDM, 2005)

Efficient model selection for regularized linear discriminant analysis. - Jieping Ye; Tao Xiong; Qi Li 001; Ravi Janardan; Jinbo Bi; Vladimir Cherkassky; Chandra Kambhamettu (CIKM, 2006)

Active learning via transductive experimental design. - Kai Yu 001; Jinbo Bi; Volker Tresp (ICML, 2006)

Computer aided detection via asymmetric cascade of sparse hyperplane classifiers. - Jinbo Bi; Senthil Periaswamy; Kazunori Okada; Toshiro Kubota; Glenn Fung; Marcos Salganicoff; R. Bharat Rao (KDD, 2006)

MILES: Multiple-Instance Learning via Embedded Instance Selection. - Yixin Chen 002; Jinbo Bi; James Ze Wang (IEEE Trans. Pattern Anal. Mach. Intell., 2006)

On the medical frontier: the 2006 KDD Cup competition and results. - Terran Lane; R. Bharat Rao; Jinbo Bi; Jianming Liang; Marcos Salganicoff (SIGKDD Explor., 2006)

A Mathematical Programming Formulation for Sparse Collaborative Computer Aided Diagnosis. - Jinbo Bi; Tao Xiong (AAAI, 2007)

Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure. - Jinbo Bi; Jianming Liang (CVPR, 2007)

Joint Optimization of Cascaded Classifiers for Computer Aided Detection. - Murat Dundar; Jinbo Bi (CVPR, 2007)

Automatic medical coding of patient records via weighted ridge regression. - Jian-Wu Xu; Shipeng Yu; Jinbo Bi; Lucian Vlad Lita; Radu Stefan Niculescu; R. Bharat Rao (ICMLA, 2007)

Learning Classifiers When the Training Data Is Not IID. - Murat Dundar; Balaji Krishnapuram; Jinbo Bi; R. Bharat Rao (IJCAI, 2007)

Robust Parametric Modeling Approach Based on Domain Knowledge for Computer Aided Detection of Vertebrae Column Metastases in MRI. - Anna K. Jerebko; Gerwin P. Schmidt; Xiang Sean Zhou; Jinbo Bi; Vikram Anand; Jiamin Liu; Stefan Schoenberg; Ingo Schmuecking; Berthold Kiefer; Arun Krishnan (IPMI, 2007)

Computer Aided Detection of Pulmonary Embolism with Tobogganing and Mutiple Instance Classification in CT Pulmonary Angiography. - Jianming Liang; Jinbo Bi (IPMI, 2007)

LungCAD: a clinically approved, machine learning system for lung cancer detection. - R. Bharat Rao; Jinbo Bi; Glenn Fung; Marcos Salganicoff; Nancy Obuchowski; David P. Naidich (KDD, 2007)

Training a CAD classifier with correlated data. - Murat Dundar; Balaji Krishnapuram; Matthias Wolf 001; Sarang Lakare; Luca Bogoni; Jinbo Bi; R. Bharat Rao (Computer-Aided Diagnosis, 2007)

Probabilistic Joint Feature Selection for Multi-task Learning. - Tao Xiong; Jinbo Bi; R. Bharat Rao; Vladimir Cherkassky (SDM, 2007)

Stratified regularity measures with Jensen-Shannon divergence. - Kazunori Okada; Senthil Periaswamy; Jinbo Bi (CVPR Workshops, 2008)

Bayesian multiple instance learning: automatic feature selection and inductive transfer. - Vikas C. Raykar; Balaji Krishnapuram; Jinbo Bi; Murat Dundar; R. Bharat Rao (ICML, 2008)

Large Scale Diagnostic Code Classification for Medical Patient Records. - Lucian Vlad Lita; Shipeng Yu; Radu Stefan Niculescu; Jinbo Bi (IJCNLP, 2008)

Reduction of lymph tissue false positives in pulmonary embolism detection. - Bernard Ghanem; Jianming Liang; Jinbo Bi; Marcos Salganicoff; Arun Krishnan (Computer-Aided Diagnosis, 2008)

An Improved Multi-task Learning Approach with Applications in Medical Diagnosis. - Jinbo Bi; Tao Xiong; Shipeng Yu; Murat Dundar; R. Bharat Rao (ECML/PKDD (1), 2008)

A min-max framework of cascaded classifier with multiple instance learning for computer aided diagnosis. - Dijia Wu; Jinbo Bi; Kim L. Boyer (CVPR, 2009)

Hierarchical learning for tubular structure parsing in medical imaging: A study on coronary arteries using 3D CT Angiography. - Le Lu 001; Jinbo Bi; Shipeng Yu; Zhigang Peng; Arun Krishnan; Xiang Sean Zhou (ICCV, 2009)

An adaptive knowledge-driven medical image search engine for interactive diffuse parenchymal lung disease quantification. - Yimo Tao; Xiang Sean Zhou; Jinbo Bi; Anna Jerebkoa; Matthias Wolf 001; Marcos Salganicoff; Arun Krishnan (Computer-Aided Diagnosis, 2009)

A Two-Level Approach Towards Semantic Colon Segmentation: Removing Extra-Colonic Findings. - Le Lu 001; Matthias Wolf 001; Jianming Liang; Murat Dundar; Jinbo Bi; Marcos Salganicoff (MICCAI (1), 2009)

Lung Nodule Detection. - Luca Bogoni; Jinbo Bi; Charles Florin; Anna K. Jerebko; Arun Krishnan; Sangmin Park; Vikas C. Raykar; Marcos Salganicoff (ImageCLEF, 2010)

Stratified learning of local anatomical context for lung nodules in CT images. - Dijia Wu; Le Lu 001; Jinbo Bi; Yoshihisa Shinagawa; Kim L. Boyer; Arun Krishnan; Marcos Salganicoff (CVPR, 2010)

Correcting Misalignment of Automatic 3D Detection by Classification: Ileo-Cecal Valve False Positive Reduction in CT Colonography. - Le Lu 001; Matthias Wolf 001; Jinbo Bi; Marcos Salganicoff (MCV, 2010)

Soliton solutions of higher-order generalized derivative nonlinear Schrödinger equation. - Jinbo Bi; Dengyuan Chen (Comput. Math. Appl., 2010)

AdaBoost on low-rank PSD matrices for metric learning. - Jinbo Bi; Dijia Wu; Le Lu 001; Meizhu Liu; Yimo Tao; Matthias Wolf 001 (CVPR, 2011)

Effective 3D object detection and regression using probabilistic segmentation features in CT images. - Le Lu 001; Jinbo Bi; Matthias Wolf 001; Marcos Salganicoff (CVPR, 2011)

Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach. - Meizhu Liu; Le Lu 001; Jinbo Bi; Vikas C. Raykar; Matthias Wolf 001; Marcos Salganicoff (MICCAI (3), 2011)

Matrix-variate and higher-order probabilistic projections. - Shipeng Yu; Jinbo Bi; Jieping Ye (Data Min. Knowl. Discov., 2011)

A multi-objective program for quantitative subtyping of clinically relevant phenotypes. - Jiangwen Sun; Jinbo Bi; Henry R. Kranzler (BIBM, 2012)

An intelligent web-based decision support tool for enhancing asthma guideline adherence. - Jinbo Bi; Arun Abraham (IHI, 2012)

1-norm support vector machine for college drinking risk factor identification. - Michael Zuba; Joseph Gilbert; Yu Wu; Jinbo Bi; Howard Tennen; Stephen Armeli (IHI, 2012)

Multi-view biclustering for genotype-phenotype association studies of complex diseases. - Jiangwen Sun; Jinbo Bi; Henry R. Kranzler (BIBM, 2013)

Quadratic optimization to identify highly heritable quantitative traits from complex phenotypic features. - Jiangwen Sun; Jinbo Bi; Henry R. Kranzler (KDD, 2013)

Efficient techniques for genotype-phenotype correlational analysis. - Subrata Saha; Sanguthevar Rajasekaran; Jinbo Bi; Sudipta Pathak (BMC Medical Informatics Decis. Mak., 2013)

A machine learning approach to college drinking prediction and risk factor identification. - Jinbo Bi; Jiangwen Sun; Yu Wu; Howard Tennen; Stephen Armeli (ACM Trans. Intell. Syst. Technol., 2013)

A sparse integrative cluster analysis for understanding soybean phenotypes. - Jinbo Bi; Jiangwen Sun; Tingyang Xu; Jin Lu 001; Yansong Ma; Lijuan Qiu (BIBM, 2014)

Identifying heritable composite traits from multivariate phenotypes and genome-wide SNPs. - Jiangwen Sun; Jinbo Bi; Henry R. Kranzler (BIBM, 2014)

Translating Effective Paper-Based Disease Management into Electronic Medical Systems. - Tingyang Xu; Jinbo Bi; Michelle M. Cloutier (ICHI, 2014)

On Multiplicative Multitask Feature Learning. - Xin Wang 023; Jinbo Bi; Shipeng Yu; Jiangwen Sun (NIPS, 2014)

Multiview Comodeling to Improve Subtyping and Genetic Association of Complex Diseases. - Jiangwen Sun; Jinbo Bi; Henry R. Kranzler (IEEE J. Biomed. Health Informatics, 2014)

Quantifying feed efficiency of dairy cattle for genome-wide association analysis. - Tingyang Xu; Jiangwen Sun; Erin E. Connor; Jinbo Bi (BIBM, 2015)

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization. - Jiangwen Sun; Jin Lu 001; Tingyang Xu; Jinbo Bi (ICML, 2015)

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction. - Tingyang Xu; Jiangwen Sun; Jinbo Bi (KDD, 2015)

Detecting tympanostomy tubes from otoscopic images via offline and online training. - Xin Wang 023; Tulio A. Valdez; Jinbo Bi (Comput. Biol. Medicine, 2015)

Learning classifiers from dual annotation ambiguity via a min-max framework. - Jinbo Bi; Xin Wang 023 (Neurocomputing, 2015)

Multi-view Bi-clustering to Identify Smartphone Sensing Features Indicative of Depression. - Asma Ahmad Farhan; Jin Lu 001; Jinbo Bi; Alexander Russell; Bing Wang 001; Athanasios Bamis (CHASE, 2016)

A Sparse Interactive Model for Matrix Completion with Side Information. - Jin Lu 001; Guannan Liang; Jiangwen Sun; Jinbo Bi (NIPS, 2016)

Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data. - Asma Ahmad Farhan; Chaoqun Yue; Reynaldo Morillo; Shweta Ware; Jin Lu 001; Jinbo Bi; Jayesh Kamath; Alexander Russell; Athanasios Bamis; Bing Wang 001 (Wireless Health, 2016)

A cross-species bi-clustering approach to identifying conserved co-regulated genes. - Jiangwen Sun; Zongliang Jiang; Xiuchun Tian; Jinbo Bi (Bioinform., 2016)

Classification of Neurological Gait Disorders Using Multi-task Feature Learning. - Ioannis Papavasileiou; Wenlong Zhang; Song Han 002; Xin Wang 023; Jinbo Bi; Nancy Byl; Masayoshi Tomizuka (CoRR, 2016)

Multiplicative Multitask Feature Learning. - Xin Wang 023; Jinbo Bi; Shipeng Yu; Jiangwen Sun; Minghu Song (J. Mach. Learn. Res., 2016)

Collaborative phenotype inference from comorbid substance use disorders and genotypes. - Jin Lu 001; Jiangwen Sun; Xinyu Wang; Henry R. Kranzler; Joel Gelernter; Jinbo Bi (BIBM, 2017)

VIGAN: Missing view imputation with generative adversarial networks. - Chao Shang; Aaron Palmer; Jiangwen Sun; Ko-Shin Chen; Jin Lu 001; Jinbo Bi (IEEE BigData, 2017)

Identifying and quantifying nonlinear structured relationships in complex manufactural systems. - Tingyang Xu; Tan Yan; Dongjin Song; Wei Cheng 002; Haifeng Chen; Geoff Jiang; Jinbo Bi (IEEE BigData, 2017)

Gait-Based Continuous Authentication Using Multimodal Learning. - Ioannis Papavasileiou; Savanna Smith; Jinbo Bi; Song Han 002 (CHASE, 2017)

Classification of Neurological Gait Disorders Using Multi-task Feature Learning. - Ioannis Papavasileiou; Wenlong Zhang; Xin Wang 023; Jinbo Bi; Li Zhang; Song Han 002 (CHASE, 2017)

A Survey on Multi-View Clustering. - Guoqing Chao; Shiliang Sun; Jinbo Bi (CoRR, 2017)

Bi-convex Optimization to Learn Classifiers from Multiple Biomedical Annotations. - Xin Wang 023; Jinbo Bi (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

Latent Sparse Modeling of Longitudinal Multi-Dimensional Data. - Ko-Shin Chen; Tingyang Xu; Jinbo Bi (AAAI, 2018)

Top-Down Indoor Localization with Wi-Fi Fingerprints Using Deep Q-Network. - Fei Dou; Jin Lu 001; Zigeng Wang; Xia Xiao; Jinbo Bi; Chun-Hsi Huang (MASS, 2018)

Reforming Generative Autoencoders via Goodness-of-Fit Hypothesis Testing. - Aaron Palmer; Dipak K. Dey; Jinbo Bi (UAI, 2018)

Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning. - Jin Lu 001; Chao Shang; Chaoqun Yue; Reynaldo Morillo; Shweta Ware; Jayesh Kamath; Athanasios Bamis; Alexander Russell; Bing Wang 001; Jinbo Bi (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018)

Large-scale Automatic Depression Screening Using Meta-data from WiFi Infrastructure. - Shweta Ware; Chaoqun Yue; Reynaldo Morillo; Jin Lu 001; Chao Shang; Jayesh Kamath; Athanasios Bamis; Jinbo Bi; Alexander Russell; Bing Wang 001 (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018)

End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion. - Chao Shang; Yun Tang 002; Jing Huang 019; Jinbo Bi; Xiaodong He 001; Bowen Zhou 001 (AAAI, 2019)

Communication-Optimal Distributed Dynamic Graph Clustering. - Chun Jiang Zhu; Tan Zhu; Kam-yiu Lam; Song Han 002; Jinbo Bi (AAAI, 2019)

Residual Deep Learning System for Mass Segmentation and Classification in Mammography. - Dina Abdelhafiz; Sheida Nabavi; Reda Ammar; Clifford Yang; Jinbo Bi (BCB, 2019)

Accelerating Large-Scale Molecular Similarity Search through Exploiting High Performance Computing. - Chun Jiang Zhu; Tan Zhu; Haining Li; Jinbo Bi; Minghu Song (BIBM, 2019)

Improved Dynamic Graph Learning through Fault-Tolerant Sparsification. - Chun Jiang Zhu; Sabine Storandt; Kam-yiu Lam; Song Han 002; Jinbo Bi (ICML, 2019)

Calibrating the Learning Rate for Adaptive Gradient Methods to Improve Generalization Performance. - Qianqian Tong; Guannan Liang; Jinbo Bi (CoRR, 2019)

On the VC-dimension of unique round-trip shortest path systems. - Chun Jiang Zhu; Kam-yiu Lam; Joseph Kee-Yin Ng; Jinbo Bi (Inf. Process. Lett., 2019)

Multi-view cluster analysis with incomplete data to understand treatment effects. - Guoqing Chao; Jiangwen Sun; Jin Lu 001; An-Li Wang; Daniel D. Langleben; Chiang-shan Ray Li; Jinbo Bi (Inf. Sci., 2019)

An Effective Hard Thresholding Method Based on Stochastic Variance Reduction for Nonconvex Sparse Learning. - Guannan Liang; Qianqian Tong; Chunjiang Zhu; Jinbo Bi (AAAI, 2020)

Towards Plausible Differentially Private ADMM Based Distributed Machine Learning. - Jiahao Ding; Jingyi Wang 002; Guannan Liang; Jinbo Bi; Miao Pan (CIKM, 2020)

Effective Proximal Methods for Non-convex Non-smooth Regularized Learning. - Guannan Liang; Qianqian Tong; Jiahao Ding; Miao Pan; Jinbo Bi (ICDM, 2020)

Predicting Outcomes of Chemical Reactions: A Seq2Seq Approach with Multi-view Attention and Edge Embedding. - Xia Xiao; Chao Shang; Jinbo Bi; Sanguthevar Rajasekaran (IJCNN, 2020)

Convolutional neural network for automated mass segmentation in mammography. - Dina Abdelhafiz; Jinbo Bi; Reda Ammar; Clifford Yang; Sheida Nabavi (BMC Bioinform., 2020)

MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks. - Yijue Wang; Chenghong Wang; Zigeng Wang; Shanglin Zhou; Hang Liu 001; Jinbo Bi; Caiwen Ding; Sanguthevar Rajasekaran (CoRR, 2020)

Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data. - Qianqian Tong; Guannan Liang; Jinbo Bi (CoRR, 2020)

Benchmark on Indexing Algorithms for Accelerating Molecular Similarity Search. - Chun Jiang Zhu; Minghu Song; Qinqing Liu; Chloé Becquey; Jinbo Bi (J. Chem. Inf. Model., 2020)

Hybrid-DCA: A double asynchronous approach for stochastic dual coordinate ascent. - Soumitra Pal 001; Tingyang Xu; Tianbao Yang; Sanguthevar Rajasekaran; Jinbo Bi (J. Parallel Distributed Comput., 2020)

Differentially Private and Communication Efficient Collaborative Learning. - Jiahao Ding; Guannan Liang; Jinbo Bi; Miao Pan (AAAI, 2021)

An Efficient Algorithm for Deep Stochastic Contextual Bandits. - Tan Zhu; Guannan Liang; Chunjiang Zhu; Haining Li; Jinbo Bi (AAAI, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (ICCAD, 2021)

Discrete Graph Structure Learning for Forecasting Multiple Time Series. - Chao Shang; Jie Chen 007; Jinbo Bi (ICLR, 2021)

Spectral vertex sparsifiers and pair-wise spanners over distributed graphs. - Chunjiang Zhu; Qinqing Liu; Jinbo Bi (ICML, 2021)

Against Membership Inference Attack: Pruning is All You Need. - Yijue Wang; Chenghong Wang; Zigeng Wang; Shanglin Zhou; Hang Liu 001; Jinbo Bi; Caiwen Ding; Sanguthevar Rajasekaran (IJCAI, 2021)

Communication Efficient Distributed Hypergraph Clustering. - Chun Jiang Zhu; Qinqing Liu; Jinbo Bi (SIGIR, 2021)

Federated Nonconvex Sparse Learning. - Qianqian Tong; Guannan Liang; Tan Zhu; Jinbo Bi (CoRR, 2021)

Escaping Saddle Points with Stochastically Controlled Stochastic Gradient Methods. - Guannan Liang; Qianqian Tong; Chunjiang Zhu; Jinbo Bi (CoRR, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search. - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Multi-view spectral graph convolution with consistent edge attention for molecular modeling. - Chao Shang; Qinqing Liu; Qianqian Tong; Jiangwen Sun; Minghu Song; Jinbo Bi (Neurocomputing, 2021)

A Bisection Reinforcement Learning Approach to 3-D Indoor Localization. - Fei Dou; Jin Lu 001; Tingyang Xu; Chun-Hsi Huang; Jinbo Bi (IEEE Internet Things J., 2021)

Asynchronous parallel stochastic Quasi-Newton methods. - Qianqian Tong; Guannan Liang; Xingyu Cai; Chunjiang Zhu; Jinbo Bi (Parallel Comput., 2021)

A Survey on Multiview Clustering. - Guoqing Chao; Shiliang Sun; Jinbo Bi (IEEE Trans. Artif. Intell., 2021)

Fusing Location Data for Depression Prediction. - Chaoqun Yue; Shweta Ware; Reynaldo Morillo; Jin Lu 001; Chao Shang; Jinbo Bi; Jayesh Kamath; Alexander Russell; Athanasios Bamis; Bing Wang 001 (IEEE Trans. Big Data, 2021)

Heterogeneous Graph Sparsification for Efficient Representation Learning. - Chandan Chunduru; Chun Jiang Zhu; Blake Gains; Jinbo Bi (BIBM, 2022)

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. - Hongwu Peng; Shaoyi Huang; Shiyang Chen 004; Bingbing Li; Tong Geng; Ang Li 006; Weiwen Jiang; Wujie Wen; Jinbo Bi; Hang Liu 001; Caiwen Ding (DAC, 2022)

Federated Optimization of ℓ0-norm Regularized Sparse Learning. - Qianqian Tong; Guannan Liang; Jiahao Ding; Tan Zhu; Miao Pan; Jinbo Bi (Algorithms, 2022)

Editorial: special issue on multi-view learning. - Guoqing Chao; Xingquan Zhu 001; Weiping Ding 001; Jinbo Bi; Shiliang Sun (Appl. Intell., 2022)

Calibrating the adaptive learning rate to improve convergence of ADAM. - Qianqian Tong; Guannan Liang; Jinbo Bi (Neurocomputing, 2022)

Mining Large-Scale Knowledge Graphs for Chemical Reaction Fingerprints. - Blake B. Gaines; Minghu Song; Jinbo Bi (IEEE Big Data, 2023)

Auto-Encoding Goodness of Fit. - Aaron Palmer; Zhiyi Chi; Derek Aguiar; Jinbo Bi (ICLR, 2023)

Customized Positional Encoding to Combine Static and Time-varying Data in Robust Representation Learning for Crop Yield Prediction. - Qinqing Liu; Fei Dou; Meijian Yang; Ezana Amdework; Guiling Wang; Jinbo Bi (IJCAI, 2023)

Polyhedron Attention Module: Learning Adaptive-order Interactions. - Tan Zhu; Fei Dou; Xinyu Wang; Jin Lu 001; Jinbo Bi (NeurIPS, 2023)

Deep statistical modelling of nanopore sequencing translocation times reveals latent non-B DNA structures. - Marjan Hosseini; Aaron Palmer; William Manka; Patrick G. S. Grady; Venkata Patchigolla; Jinbo Bi; Rachel J. O'Neill; Zhiyi Chi; Derek Aguiar (Bioinform., 2023)

Stochastic privacy-preserving methods for nonconvex sparse learning. - Guannan Liang; Qianqian Tong; Jiahao Ding; Miao Pan; Jinbo Bi (Inf. Sci., 2023)

Editorial: Special Issue on Transfer Learning. - Guoqing Chao; Xingquan Zhu 001; Weiping Ding 001; Jinbo Bi; Shiliang Sun (Neural Process. Lett., 2023)

Predicting Symptom Improvement During Depression Treatment Using Sleep Sensory Data. - Chinmaey Shende; Soumyashree Sahoo; Stephen Sam; Parit Patel; Reynaldo Morillo; Xinyu Wang; Shweta Ware; Jinbo Bi; Jayesh Kamath; Alexander Russell; Dongjin Song; Bing Wang 001 (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2023)

Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement. - Soumyashree Sahoo; Chinmaey Shende; Md. Zakir Hossain; Parit Patel; Xinyu Wang; Md Ishtyaq Mahmud; Jinbo Bi; Jayesh Kamath; Alexander Russell; Dongjin Song; Bing Wang 001 (CHASE, 2024)

Unsupervised Bayesian change point detection model to track acute stress responses. - Hossein Hamidi Shishavan; Ethan Gossett; Jinbo Bi; Robert Henning; Martin Cherniack; Insoo Kim (Biomed. Signal Process. Control., 2024)

Distilling Adversarial Robustness Using Heterogeneous Teachers. - Jieren Deng; Aaron Palmer; Rigel Mahmood; Ethan Rathbun; Jinbo Bi; Kaleel Mahmood; Derek Aguiar (CoRR, 2024)

Weakly Supervised Change Detection via Knowledge Distillation and Multiscale Sigmoid Inference. - Binghao Lu; Caiwen Ding; Jinbo Bi; Dongjin Song (CoRR, 2024)

Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness. - Jieren Deng; Hanbin Hong; Aaron Palmer; Xin Zhou 017; Jinbo Bi; Kaleel Mahmood; Yuan Hong 001; Derek Aguiar (CoRR, 2024)

On-Device Indoor Positioning: A Federated Reinforcement Learning Approach With Heterogeneous Devices. - Fei Dou; Jin Lu 001; Tan Zhu; Jinbo Bi (IEEE Internet Things J., 2024)

Explaining Graph Neural Networks with mixed-integer programming. - Blake B. Gaines; Chunjiang Zhu; Jinbo Bi (Neurocomputing, 2025)

Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory Data on Smartphones. - Soumyashree Sahoo; Chinmaey Shende; Md. Zakir Hossain; Parit Patel; Yushuo Niu; Xinyu Wang; Shweta Ware; Jinbo Bi; Jayesh Kamath; Alexander Russell; Dongjin Song; Qian Yang; et al. (CoRR, 2025)

Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks. - Xin Wang 023; Jinbo Bi; Minghu Song (CoRR, 2025)

Unraveling the Potential of Diffusion Models in Small Molecule Generation. - Peining Zhang; Daniel Baker; Minghu Song; Jinbo Bi (CoRR, 2025)