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Rong Jin's Publications List
[Machine Learning] [Information Retrieval and Natural Language Processing] [Compute Vision and Multimedia] [Bioinformatics]
--- Machine Learning ---
  • Regret Bounded by Variation for Online Convex Optimization
    T. Yang, M. Mahdavi, R. Jin and S.H. Zhu, Machine Learning, 2013
  • Online Multiple Kernel Classification
    S. Hoi, R. Jin, P. Zhao, and T. Yang, Machine Learning, 90(2): 289-316, 2013
  • Improved Bounds for the Nystrom Method With Application to Kernel Classification
    R. Jin, T. Yang, M. Mahdavi, Y.-F. Li, and Z.-H. Zhou, IEEE Transactions on Information Theory, 59(10): 6939-6949, 2013
  • Inferring User's Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach
    J. Yi, R. Jin, S. Jain, and A. K. Jain, Conference on Human Computation & Crowdsourcing (HCOMP), 2013
  • Passive Learning with Target Risk
    M. Mahdavi and R. Jin, Conference of Learning Theory (COLT), 2013
  • Recovering Optimal Solution by Dual Random Projection
    L. Zhang, M. Mahdavi, R. Jin, T. Yang, and S.H. Zhu, Conference of Learning Theory (COLT), 2013
  • Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion
    J. Yi, L. Zhang, R. Jin, Q. Qian, and A. Jain, International Conference on Machine Learning (ICML), 2013
  • O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions
    L. Zhang, T. Yang, R. Jin, and X. He, International Conference on Machine Learning (ICML), 2013
  • One-Pass AUC Optimization
    W. Gao, R. Jin, S. H. Zhu, and Z.-H. Zhou, International Conference on Machine Learning (ICML), 2013
  • Online Kernel Learning with a Near Optimal Sparsity Bound
    L. Zhang, J. Yi, R. Jin, M. Lin, and X. He, International Conference on Machine Learning (ICML), 2013
  • Stochastic Convex Optimization with Multiple Objectives
    M. Mahdavi, T. Yang, and R. Jin, Advance in Neural Information Processing Systems (NIPS), 2013
  • Speedup Matrix Completion with Side Information: Application to Multi-Label Learning
    M. Xu, R. Jin, and Z.-H. Zhou,  Advance in Neural Information Processing Systems (NIPS), 2013
  • Mixed Optimization for Smooth Functions
    M. Mahdavi, L. Zhang, and R. Jin,  Advance in Neural Information Processing Systems (NIPS), 2013
  • Linear Convergence with Condition Number Independent Access of Full Gradients
    L. Zhang, M. Mahdavi, and R. Jin,  Advance in Neural Information Processing Systems (NIPS), 2013
  • Learning Bregman Distance Functions for Semi-Supervised Clustering
    L. Wu, S. C. H. Hoi, R. Jin, J. Zhu, and N. Yu,  IEEE Trans. Knowl. Data Eng. 24(3): 478-491, 2012
  • Multiple Kernel Learning from Noisy Labels by Stochastic Programming
    T. Yang and R. Jin,  International Conference on Machine Learning (ICML), 2012
  • A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error Bound
    T. Yang, M. Ji, and R. Jin,  International Conference on Machine Learning (ICML), 2012
  • Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning
    S. C. H. Hoi and R. Jin,  International Conference on Machine Learning (ICML), 2012
  • Efficient Online Learning for Large-scale Sparse Kernel Logistic Regression
    L. Zhang, R. Jin, J. Bu, C. Chen, and X. He,  AAAI Conference on Artificial Intelligence (AAAI), 2012
  • Online Kernel Selection: Algorithms and Evaluations
    T. Yang, R. Jin, and M. Mahdavi,  AAAI Conference on Artificial Intelligence (AAAI), 2012
  • Random Projection with Filtering for Nearly Duplicate Search
    T. Y. Lin, R. Jin, D. Cai, and X. He,  AAAI Conference on Artificial Intelligence (AAAI), 2012
  • Online Optimization with Gradual Variations
    T. Yang, M. Mahdavi, R. Jin, and S. Zhu,  Conference of Learning Theory (COLT), 2012
  • Nystrom Method vs Random Fourier Features: A Theoretical and Empirical Comparison
    T. Yang, Y. Li, M. Mahdavi, R. Jin,  Advance in Neural Information Processing Systems (NIPS), 2012
  • Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning
    J. Yi, R. Jin, A. Jain, and S. Jain,  Advance in Neural Information Processing Systems (NIPS), 2012
  • Stochastic Gradient Descent with Only One Projection
    M. Mahdavi, T. Yang, R. Jin, S. Zhu,  Advance in Neural Information Processing Systems (NIPS), 2012
  • Crowdclustering with Sparse Pairwise Labels: A Matrix Completion Approach
    J. Yi, R. Jin, A. K. Jain, and S. Jain,  Proceedings of the 4th Human Computation Workshop in junction with AAAI, 2012
  • Efficient Kernel Clustering Using Random Fourier Features
    R. Chitta, R. Jin and A. K. Jain,  International Conference on Data Mining (ICDM), 2012
  • Robust Ensemble Clustering by Matrix Completion
    J. Yi, T. Yang, R. Jin, A. K. Jain, and M. Mahdavi,  International Conference on Data Mining (ICDM), 2012
  • Double Updating Online Learning
    P. Zhao, S. C. H. Hoi, and R. Jin,  Journal of Machine Learning Research 12: 1587-1615, 2011
  • Detecting communities and their evolutions in dynamic social networks - a Bayesian approach
    T. Yang, Y. Chi, S. Zhu, Y. Gong, and R. Jin,  Machine Learning 82(2): 157-189, 2011, 2011
  • Learning to trade off between exploration and exploitation in multiclass bandit prediction
    H. Valizadegan, R. Jin, S. Wang,  ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2011
  • Approximate kernel k-means: solution to large scale kernel clustering
    R. Chitta, R. Jin, T. C. Havens, A. K. Jain,  ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2011
  • Multi-Task Learning in Square Integrable Space
    W. Wu, H. Li, Y. Hu, and R. Jin,  AAAI Conference on Artificial Intelligence (AAAI), 2011
  • Online AUC Maximization
    P. Zhao, S. C.H. Hoi, R. Jin, and T. Yang,  International Conference on Machine Learning (ICML), 2011
  • Multi-label Learning with Incomplete Class Assignments
    S. S. Bucak, R. Jin, and A. K. Jain,  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011
  • Exclusive Lasso for Multi-task Feature Selection
    Y. Zhou, R. Jin, and S. C. H. Hoi,  International Conference on Artificial Intelligence and Statistics (AISTAT), 2010
  • Exclusive Lasso for Multi-task Feature Selection
    Y. Zhou, R. Jin, and S. C. H. Hoi,  International Conference on Artificial Intelligence and Statistics (AISTAT), 2010
  • Online Multiple Kernel Learning: Algorithms and Mistake Bounds
    R. Jin, S. C. H. Hoi, and T. Yang,  International Conference on Algorithmic Learning Theory (ALT), 2010
  • Learning from Noisy Side Information by Generalized Maximum Entropy Model
    T. Yang, R. Jin, and A. K. Jain, International Conference on Machine Learning (ICML), 2010
  • Simple and Efficient Multiple Kernel Learning By Group Lasso
    Z. Xu, R. Jin, H. Yang, I. King, and M. Lyu, International Conference on Machine Learning (ICML), 2010
  • Unsupervised Transfer Learning: Application to Text Categorization
    T. Yang, R. Jin, and A. K. Jain, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2010
  • Exploitation and Exploration in a Performance based Contextual Advertising System
    W. Li, X. Wang, R. Zhang, Y. Cui, R. Jin, and J.C. Mao, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2010
  • Smooth Optimization for Effective Multiple Kernel Learning
    Z. Xu,  R. Jin, S. Zhu, M. Lyu, and I. King, AAAI Conference on Artificial Intelligence (AAAI), 2010
  • Robust Metric Learning with Smooth Optimization
    K. Huang, R. Jin, Z. Xu, and C. Liu, Conference on Uncertainty in Artificial Intelligence (UAI), 2010
  • Directed Network Community Detection: A Popularity and Productivity Link Model
    T. Yang, Y. Chi, S. Zhu, Y. Gong, and R. Jin, SIAM International Conference on Data Mining (SDM), 2010
  • Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition
    S. Bucak, R. Jin, and A. K. Jain, Advance in Neural Information Processing Systems (NIPS), 2010
  • Active Learning by Querying Informative and Representative Examples
    S. Huang, R. Jin, and Z. H. Zhou, Advance in Neural Information Processing Systems (NIPS), 2010
  • Efficient Algorithm for Localized Support Vector Machine
    H. Cheng, P. N. Tan and R. Jin, IEEE Transaction on Knowledge and Data Engineering (TKDE), 22(4): 537-549, 2010
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  • Semi-supervised Feature Selection based on Manifold Regularization
    Z. Xu, I. King, M. Lyu, and R. Jin, IEEE Transaction on Neural Networks,1033-1047, 2010
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  • Learning Bregman Distance Functions for Semi-Supervised Clustering
    L. Wu, S. C. H. Hoi, R. Jin, Jianke Zu, and Nenghai Yu, IEEE Transactions on Knowledge and Data Engineering (TKDE), (in press)
    		•
    • SemiBoost: Boosting for Semi-supervised Learning
      P. K. Mallapragada, R. Jin, A. K. Jain, and Y. Liu, IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI), 31(11):2000-2014, 2009
  • Batch Mode Active Learning with Applications to Text Categorization and Image Retrieval
    S. C. H. Hoi, R. Jin, and M. R. Lyu, IEEE Transaction on Knowledge and Data Engineering (TKDE), 21(9): 1233-1248, 2009
    • DUOL: A Double Updating Approach for Online Learning
      P. Zhao, S. C. H. Hoi and R. Jin, Advance in Neural Information Processing Systems (NIPS), 2009
    • Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering
      L. Wu, R. Jin, S. C. H. Hoi, J. Zhu and N. Yu, Advance in Neural Information Processing Systems (NIPS), 2009
    • Learning to Rank by Optimizing NDCG Measure
      H. Valizadegan, R. Jin, R. Zhang and J. Mao, Advance in Neural Information Processing Systems (NIPS), 2009
    • Regularized Distance Metric Learning:Theory and Algorithm
      R. Jin and S. Wang, Advance in Neural Information Processing Systems (NIPS), 2009
    • Adaptive Regularization for Transductive Support Vector Machine
      Z. Xu, R. Jin, J. Zhu, I. King, M. R. Lyu and Z. Yang, Advance in Neural Information Processing Systems (NIPS), 2009
    • Efficient Multi-label Ranking for Multi-class Learning: Application to Object Recognition
      S. S. Bucak, P. K. Mallapragada, R. Jin and A. K Jain, IEEE International Conference on Computer Vision (ICCV), 2009
    • Combining Link and Content for Community Detection: A Discriminative Approach
      T. Yang, R. Jin, Y. Chi and S. Zhu, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2009
    • Learning a Distance Metric from Multi-instance Multi-label Data
      R. Jin, S. Wang, and Z.-H. Zhou, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2009
    • A Bayesian Framework for Community Detection Integrating Content and Link
      T. Yang, R. Jin, Y. Chi and S. Zhu, Conference on Uncertainty in Artificial Intelligence (UAI), 2009
    • Online Learning by Ellipsoid Method
      L. Yang, R. Jin and J. Ye, International Conference on Machine Learning (ICML), 2009
    • Non-monotonic Feature Selection
      Z. Xu, R. Jin, J. Ye, M. R. Lyu and I. King, International Conference on Machine Learning (ICML), 2009
    • A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks
      T. Yang, Y. Chi, S. Zhu, Y. Gong and R. Jin, SIAM International Conference on Data Mining (SDM), 2009
    • An Information Geometry Approach for Distance Metric Learning
      S. Wang and R. Jin, International Conference on Artificial Intelligence and Statistics (AISTAT), 2009
    • An Extended Level Method for Efficient Multiple Kernel Learning 
      Z. Xu, R. Jin, I. King, and M. Lyu, Advance in Neural Information Processing Systems (NIPS), 2008
    • Multi-label Multiple Kernel Learning 
      S. Ji, L. Sun, R. Jin, and J. Ye, Advance in Neural Information Processing Systems (NIPS), 2008
    • Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization 
      L. Yang, R. Jin and R. Sukthankar, Advance in Neural Information Processing Systems (NIPS), 2008
    • Semi-supervised Boosting for Multi-Class Classification
      H. Valizadegan, R. Jin and A. K. Jain, European Conference on Machine Learning (ECML), 2008
    • Semi-Supervised Ensemble Ranking
      S. C. H. Hoi and R. Jin, AAAI Conference on Artificial Intelligence (AAAI), 2008
    • Active Kernel Learning
      S. C. H. Hoi and R. Jin, International Conference on Machine Learning (ICML), 2008
    • Efficient Convex Relaxation for Transductive Support Vector Machine
      Z. Xu, R. Jin, J. Zhu, I. King, and M. R. Lyu, Advance in Neural Information Processing Systems (NIPS), 2007 
    • Multi-Class Learning by Smoothed Boosting
      R. Jin and J. Zhang, Machine Learning 67(3):207-227, 2007
    • BoostCluster: Boosting Clustering by Pairwise Constraints
      Y. Liu, R. Jin ,and A. K. Jain, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2007
    • A Learning Framework using Green's Function and Kernel Regularization with Application to Recommender System
      C. Ding, R. Jin,T. Li, and H. Simon, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2007
    • Semi-supervised Learning by Mixed Label Propagation
      W. Tong and R. Jin, AAAI Conference on Artificial Intelligence (AAAI), 2007
    • Active Algorithm Selection
      F. Chen and R. Jin, AAAI Conference on Artificial Intelligence (AAAI), 2007
    • Learning Nonparametric Kernel Matrices from Pairwise Constraints
      S. C. Hoi, R. Jin, J. Zhu and M. R. Lyu, International Conference on Machine Learning (ICML), 2007
    • Bayesian Active Distance Metric Learning
      L. Yang, R. Jin and R. Sukthankar, Conference on Uncertainty in Artificial Intelligence (UAI), 2007
    • Localized Support Vector Machine and Its Efficient Algorithm
      H. Cheng, P. N. Tan and R. Jin, SIAM Conference on Data Mining (SDM), 2007
    • Generalized Maximum Margin Clustering and Unsupervised Kernel Learning
      H. Valizadegan and R. Jin, Advance in Neural Information Processing Systems (NIPS), 2006
    • Correlated Label Propagation with Application to Multi-label Learning
      F. Kang, R. Jin and R. Sukthankar, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2006
    • Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization
      Y. Liu, R. Jin and L. Yang,  AAAI Conference on Artificial Intelligence (AAAI), 2006
    • An Efficient Algorithm for Local Distance Metric Learning
      L. Yang, R. Jin , R. Sukthankar and Yi Liu, AAAI Conference on Artificial Intelligence (AAAI), 2006
    • Batch Mode Active Learning and Its Application to Medical Image Classification
      S. C. H. Hoi, R. Jin ,J. Zhu, and M. R. Lyu, International Conference on Machine Learning (ICML), 2006
    • Large-scale Text Categorization by Batch Mode Active Learning
      S. C. H. Hoi, R. Jin and M. R. Lyu, International Conference on World Wide Web (WWW), 2006
    • A Probabilistic Approach for Optimizing Spectral Clustering
      R. Jin, C.Ding and F. Kang, Advance in Neural Information Processing Systems (NIPS), 2005
    • Learn to Weight Terms in Information Retrieval Using Category Information
      R. Jin, J. Y. Chai and L. Si, International Conference on Machine Learning (ICML), 2005
    • A Smoothed Boosting Algorithm Using Probabilistic Output Codes
      R. Jin and J. Zhang, International Conference on Machine Learning (ICML), 2005
    • Learning with Labeled Sessions
      R. Jin, H. Liu, and F. Kang, International Joint Conference on Artificial Intelligence (IJCAI), 2005
    • A Novel Approach to Model Generation for Heterogeneous Data Classification
      R. Jin and H. Liu, International Joint Conference on Artificial Intelligence (IJCAI), 2005
    • Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis
      L. Si and R. Jin, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2005
    • A Framework for Incorporating Class Priors into Discriminative Classification
      R. Jin and Y. Liu, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2005
    • Ordering Patterns by Combining Opinions from Multiple Sources
      P. N. Tan and R. Jin, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2004
    • A Bayesian Approach toward Active Learning for Collaborative Filtering
      R. Jin and L. Si, Conference on Uncertainty in Artificial Intelligence (UAI), 2004
    • Robust Feature Induction for Support Vector Machines
      R. Jin and H. Liu, International Conference on Machine Learning (ICML), 2004
    • A New Pairwise Ensemble Approach for Text Classification
      Y. Liu, J. Carbonell and R. Jin, European Conference on Machine Learning (ECML), 2003
    • A New Boosting Algorithm using Input Dependent Regularizer
      R. Jin, Liu, Y., L. Si, J. Carbonell and A. Hauptmann, International Conference on Machine Learning (ICML), 2003
    • A Faster Iterative Scaling Algorithm For Conditional Exponential Model
      R. Jin,  R. Yan, and J. Zhang, International Conference on Machine Learning (ICML), 2003
    • Modified Logistic Regression: An Approximation to SVM and its Applications in Large-Scale Text Categorization 
      J. Zhang, R. Jin, Y. Yang, and A. Hauptmann, International Conference on Machine Learning (ICML), 2003
    • Learning with Multiple Labels
      R. Jin and Z. Ghahramani, Advance in Neural Information Processing Systems (NIPS), 2003
    --- Information Retrieval and Natural Language Processing ---    Back To Top
  • Semi-Supervised SVM Batch Mode Active Learning with Applications to Image Retrieval
    S. Hoi, R. JinJ. Zhu, and M. R. Lyu, ACM Transaction on Information System (TOIS) 27(3),July, 2009
    • Representative Entry Selection for Profiling Blogs
      J. Zhuang, S. Hoi, A. Sun, and R. Jin, ACM Conference on Information and Knowledge Management (CIKM), 2008
    • Ranking Refinement and Its Application to Information Retrieval
      R. Jin ,H. Valizadegan, and L. Hang, International World Wide Web Conference (WWW), 2008
    • An Empirical Investigation of User Term Feedback in Targeted Image Search via Text-based Retrieval,
      J. Chai, C. Zhang, and R. Jin, ACM Transactions on Information Systems (TOIS), 25(1), 2007
    • Automated Vocabulary Acquisition and Interpretation in Multimodal Conversational Systems
      Y. Liu, J. Chai and R. Jin, Annual Meeting of the Association for Computational Linguistics (ACL), 2007
    • Semi-supervised Collaborative Text Classification
      M. Wu, R. Jin, and R. Sukthankar, European Conference on Machine Learning (ECML), 2007
    •  A Statistical Framework for Query Translation Disambiguation.
      Y. Liu, R. Jin, and J. Chai, ACM Transactions on Asian Language Information Processing (TALIP), 5(4): 360-387, 2006
    • A Graph-based Framework for Relation Propagation and Its Application to Multi-label Learning
      M. Wu and R. Jin, Annual International ACM SIGIR Conference (SIGIR), 2006
    • A Study of Mixture Models for Collaborative Filtering
      R. Jin, L. Si and C. X. Zhai, Information Retrieval Journal, 9(3):57-382, 2006
    • Study of Cross Lingual Information Retrieval Using On-line Translation Systems
      R. Jin and J. Y. Chai, Annual International ACM SIGIR Conference (SIGIR), 2005
    • User Term Feedback in Interactive Text-based Image Retrieval
      C. Zhang, J. Y. Chai, and R. Jin, Annual International ACM SIGIR Conference (SIGIR), 2005
    • A Maximum Coherence Model for Dictionary-based Cross-language Information Retrieval
      L. Yi and R. Jin, Annual International ACM SIGIR Conference (SIGIR), 2005
    • Query Translation Disambiguation As Graph Partitioning
      L. Yi and R. Jin,  AAAI Conference on Artificial Intelligence (AAAI), 2005
    • Unified Filtering by Combining Collaborative Filtering and Content-Based Filtering via Mixture Model and Exponential Model
      L. Si and R. Jin, ACM Conference on Information and Knowledge Management (CIKM), 2004
    • An Automated Weighting Scheme for Collaborative Filtering
      R. Jin, J. Y. Chai and L. Si, Annual International ACM SIGIR Conference (SIGIR), 2004
  • Discourse Status for Context Questions
    J. Y. Chai and R. Jin, HLT-NAACL 2004 Workshop on Pragmatics in Question Answering, 2004
    • A Study of Methods for Normalizing User Ratings in Collaborative Filtering
      R. Jin and L. Si, Annual International ACM SIGIR Conference (SIGIR), 2004
    • Collaborative Filtering with Decoupled Models for Preferences and Ratings
      R. Jin, L. Si, C.X. Zhai, and J. Callan, International Conference on Information and Knowledge Management (CIKM), 2003
  • Information Retrieval for OCR Documents: A Content-based Probabilistic Correction Model  
    R. Jin, C. X. Zhai and Hauptmann, A. Electronic Imaging Conference,(EI'03) Document Recognition and Retrieval Conference, 2003
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    • A New Probabilistic Model for Title Generation
      R. Jin and A. Hauptmann, International Conference On Computational Linguistics (COLING 2002), 2002
    • A Language Model Framework for Resource Selection and Results Merging
      L. Si, R. Jin, J. Callan and P. Ogilvie, International Conference on Information and Knowledge Management (CIKM), 2002
    • Title language model for information retrieval
      R. Jin, C. X. Zhai, and A. Hauptmann, Annual International ACM SIGIR Conference (SIGIR), 2002
    • Language Model for IR Using Collection Information
      R. Jin, L. Si and A. Hauptmann and J. Callan, Annual International ACM SIGIR Conference (SIGIR), 2002
    • Meta-scoring: Automatically Evaluating Term Weighting Schema in IR without Precision-Recall
      R. Jin, C. Faloutsos  and A. Hauptmann, Annual International ACM SIGIR Conference (SIGIR), 2001
    • Probabilistic Combination of Content and Links
      R. Jin and S. Dumais, Annual International ACM SIGIR Conference (SIGIR), 2001
    • Title Generation for Machine-Translated Documents
      R. Jin       and A. Hauptmann, International Joint Conference on Artificial Intelligence (IJCAI), 2001
    • Automatic Title Generation for Spoken News
      R. Jin       and A. Hauptmann, Human Language Technology conference (HLT), 2001
    • Title Generation for Spoken Broadcast News using a Training Corpus
      R. Jin and A. Hauptmann, International Conference of Spoken Language Processing (Interspeech), 2000
    --- Computer Vision and Multimedia ---    Back To Top
    • Multiple Kernel Learning for Visual Object Recognition: A Review
      S. S. Bucak, R. Jin, and A. K. Jain, IEEE Trans. Pattern Anal. Mach. Intell., 2013
    • Online Multiple Kernel Ranking for Visual Similarity Search
      X. Hao, P. Zhao, S. Hoi, and R. Jin, IEEE Trans. Pattern Anal. Mach. Intell., 2013
    • Tag Completion for Image Retrieval
      L. Wu, R. Jin, and A. K. Jain, IEEE Trans. Pattern Anal. Mach. Intell., 35(3): 716-727, 2013
    • Tattoo Image Matching and Retrieval
      A. K. Jain, R. Jin, and J.-E. Lee, IEEE Computer 45(5): 93-96, 2012
    • Image Retrieval in Forensics: Tattoo Image Database Application
      J. E. Lee, R. Jin, A. K. Jain, and W. Tong,  IEEE Multimedia 19(1): 40-49, 2012
    • Distance metric learning from uncertain side information for automated photo tagging
      L. Wu, S. C. H. Hoi, R. Jin, J. Zhu, and N. Yu,  ACM Transactions on Intelligent Systems and Technology (TIST) 2(2): 13, 2011
    • Active multiple kernel learning for interactive 3D object retrieval systems
      S. C. H. Hoi and R. Jin,  ACM Transactions on Interactive Intelligent Systems (TiiS) 1(1): 3, 2011
  • Multi-label Learning with Incomplete Class Assignments
    S. S. Bucak, R. Jin, and A. K. Jain,  Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011), 2011
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    • Online Visual Vocabulary Pruning Using Pairwise Constraints
      P. K. Mallapragada, R. Jin, A. K. Jain,, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010
  • A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval
    L. Yang, R. Jin, L. Mummert, R. Sukthankar, A. Goode, B. Zheng,, S. Hoi, and M. Satya-narayanan, IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI) 32(1):30-44, 2010
    • Distance Metric Learning from Uncertain Side Information with Application to Automated Photo Tagging
      L. Wu, S. C.H. Hoi, R. Jin, J. Zhu and N. Yu, ACM International Conference on Multimedia (MM2009), 2009
    • Scars, Marks and Tattoos (SMT): Soft Biometric for Suspect and Victim Identification,
      J-E. Lee, A. K. Jain, and R. Jin, Biometric Symposium, BCC, 2008 (Best Paper Award)
    • Semi-Supervised SVM Batch Mode Active Learning for Image Retrieval
      S. C. H. Hoi, R. Jin ,J. Zhu and M. Lyu, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2008
    • Unifying Discriminative Visual Codebook Generation with Classifier Training for Object Category Recognition
      L. Yang, R. Jin ,R. Sukthankar and F. Jurie, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2008
    • Rank-based Distance Metric Learning: An Application to Image Retrieval
      J.E. Lee, R. Jin and A.K. Jain, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2008
    • Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data
      L. Yang, R. Jin, and R. Sukthankar, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2007
    • Tattoo-ID: Automatic Tattoo Image Retrieval for Suspect and Victim Identification,
      A. K. Jain, J. Lee and R. Jin, Pacific Rim Conference on Multimedia (PCM 2007), 2007 (Best Paper Award)
    • Collaborative Image Retrieval via Regularized Metric Learning
      L. Si, R. Jin, S. C.H. Hoi and Michael R. Lyu, ACM Multimedia Systems Journal, 2006
  • Symmetric Statistical Translation Models for Automatic Image Annotation,
    F. Kang and R. Jin, Proceedings of the 2005 SIAM Conference on Data Mining (SDM 2005), 2005
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    • A Unified Log-Based Relevance Feedback Scheme for Image Retrieval
      S. C. H. Hoi, M. R. Lyu and R. Jin, IEEE Transactions on Knowledge and Data Engineering Journal (TKDE) 18(4): 509-524, 2006
    • Linguistic Theories in Efficient Multimodal Reference Resolution: an Empirical Investigation
      V. Bansal, C. Zhang, J. Y. Chai and R. Jin, International Conference on Intelligent User Interfaces (IUI), 2005
    • Regularizing Translation Models for Better Automatic Image Annotation
      F. Kang, R. Jin, and J. Y. Chai, ACM Conference on Information and Knowledge Management (CIKM), 2004
    • Automatic Image Annotation via Coherent Language Model and Active Learning
      R. Jin, J. Y. Chai, and L. Si, ACM Annual Conference on Multimedia (MM), 2004
    • Preference-based Graphic Models for Collaborative Filtering
      R. Jin, L. Si and C.X. Zhai, Conference on Uncertainty in Artificial Intelligence (UAI), 2003
    • Flexible Mixture Model for Collaborative Filtering
      L. Si and R. Jin, International Conference on Machine Learning (ICML), 2003
    • Negative Pseudo-Relevance Feedback in Content-based Video Retrieval
      R. Yan, A. Hauptmann, and R. Jin, Annual ACM International Conference on Multimedia (MM), 2003
    --- Bioinformatics ---    Back To Top
    • Cis-regulatory code of stress-responsive transcription in Arabidopsis thaliana
      C. Zou, K. Suna, J. D. Mackalusoa, A. E. Seddona, R. Jin, M. F. Thomashowd, and S. H. Shiu,  Proceedings of the National Academy of Sciences (PNAS), 108(36):14992-14997, 2011
  • Identifying Functional Connectivity in Large Scale Neural Ensemble Recordings: A Multiscale Data Mining Approach
    S. Eldawlatly, R. Jin, and K. Oweiss, Neural Computation 21(2): 450-477 (2009)
  • Reconstruct Modular Phenotype-specific Gene Networks by Knowledge-Driven Matrix Factorization
    X. Yang, Y. Zhou, R. Jin and C. Chan, Bioinformatics 25(17): 2236-2243, 2009
    • Automated Annotation of Drosophila Gene
      S. Li, L. Sun, R. Jin, S. Kumar, and J. Ye, Binformatics 24(17):1881-1888, 2008
    • Using Knowledge Driven Matrix Factorization to Reconstruct Modular Gene Regulatory Network
      Y. Zhou, Z. Li, X. Yang, L. Zhang, S. Srivastava and R. Jin, C. Chan, AAAI Conference on Artificial Intelligence (AAAI), 2008
  • Identifying Neuronal Assemblies with Local and Global Connectivity with Scale Space Spectral Clustering
    K. Oweiss, R. Jin, and Y. Suhail, Neurocomputing,70(10-12): 1728-1734,2006
    • A Mixture Model for Spike Train Ensemble Analysis Using Spectral Clustering
      R. Jin, Y. Suhail and K. Oweiss, IEEE Int. Conf. Acoustics, Speech & Signal Processing (ICASSP), 2006


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    Copyright By Rong Jin CSE,MSU