Some Publications Related to NSF grant

Small: Simultaneous Decomposition and Predictive Modeling on Large Multi-Modal Data

Softcopies of a majority of these publications are available from

http://www.ideal.ece.utexas.edu/pub.html

or through Google Scholar

http://scholar.google.com/citations?user=Xnk4W5cAAAAJ&hl=en

Refereed Archival Journal Publications

• M. Deodhar and J. Ghosh, “SCOAL: A Framework for Simultaneous Co-Clustering and Learning from Complex Data”, in ACM Transactions on Knowledge Discovery from Data. 4(3), Oct 2010, pp. 11:1-11:31
• J. Ghosh and A. Acharya, “Cluster Ensembles”, WIREs Data Mining and Knowledge Discovery 1 (4), July/Aug 2011, pp. 305-315.
• Thiago F. Covoes, Eduardo R. Hruschka and Joydeep Ghosh, “A Study of K-Means-Based Algorithms for Constrained Clustering”, in Intelligent Data Analysis, 17(3), 2013, pp. 485-505.
• Thiago F. Covoes, Eduardo R. Hruschka and Joydeep Ghosh, "Competitive Learning with Pairwise Constraints Derived from Labeled Data", in IEEE Transactions on Neural Networks and Learning Systems, 24(1): 164-169 (2013)
• Y. Park and J. Ghosh, "CUDIA: Probabilistic Cross-level Imputation using Individual Auxiliary Information", ACM Transactions on Intelligent Systems and Technology, spl. Issue on Health Informatics, 4(3), 2013, pp. 66:1 – 66:24.
• Y. Park and J. Ghosh, “Ensemble of a -Trees for Imbalanced Classification Problems”, in IEEE Trans. Knowledge and Data Engineering, 26(1), Jan 2014, pp. 131-143.
• A. Acharya, E.R. Hruschka and J. Ghosh, An Optimization Framework for Semi-Supervised and Transfer Learning using Multiple Classifiers and Clusterers, ACM Transactions on Knowledge Discovery from Data, 2014

· J. Ho, Joydeep Ghosh; Steve Steinhubl; Walter Stewart; Joshua C Denny; Bradley  A Malin; Jimeng Sun “Limestone: High-throughput Candidate Phenotype Generation via Tensor Factorization”, in Jl. Of Biomedical Informatics,

· O. Koyejo, C. Lee and J. Ghosh, "A Constrained Matrix-Variate Gaussian Process for Transposable Data", in Machine Learning Journal,

Book Chapters

· Acharya, E.R. Hruschka, J. Ghosh and S. Acharyya, “C3E: A Framework for Combining Ensembles of Classifiers and Clusterers”, in Multiple Classifier Systems, C. Sansone, J. Kittler and F. Roli (Eds.), LNCS Vol. 6713, Springer, pp. 86-95, 2011.

• Y. Park and J. Ghosh, “Compact Ensemble Trees for Imbalanced Data”, in Multiple Classifier Systems, C. Sansone, J. Kittler and F. Roli (Eds.), LNCS Vol. 6713, Springer, pp. 269-278, 2011.
• J. Ghosh and G Gupta, “Bregman Bubble Clustering: A Robust Framework for Mining Dense Clusters”, in DATA MINING: Foundations and Intelligent Paradigms Volume 1: Clustering, Association and Classification, Dawn Holmes and Lakhmi C. Jain (Eds), Springer, 2012, pp. 157-208.
• J. Ghosh and A. Sharma, “Actionable Mining of Large, Multi-relational Data using Localized Predictive Models”, in Knowledge Discovery, Knowledge Engineering and Knowledge Management, Revised Selected Papers Series: Communications in Computer and Information Science, Vol. 272, Fred, A.; Dietz, J. L. G.; Liu, K.; Filipe, J. (Eds.), Springer, 2013, pp. 3-22.
• A. Acharya and J. Ghosh, “Cluster Ensembles: Theory and Applications”, in Data Clustering: Algorithms and Applications, Chandan Reddy and Charu Aggarwal (Eds), CRC Press, 2014, Ch 22, pp. 551-570.

Conference/Workshop Proceedings

• A. Sharma, Meghana Deodhar, Joydeep Ghosh, “A Semi-Supervised Approach for Handling Cold-Start in Recommender Systems”, in SCECR 2010, Austin, June 2010.
• M Deodhar and J Ghosh,"A Decoupled Approach for Modeling Heterogeneous Dyadic Data with Covariates" IEEE Symposium on Foundations and Practice of Data Mining in GrC2010. Proc. 2010 IEEE International Conference on Granular Computing (GrC 2010), San Jose, Aug 2010
• M Deodhar, C. Jones and J Ghosh,"Parallel Simultaneous Co-clustering and Learning with Map-Reduce”, Proc. 2010 IEEE International Conference on Granular Computing (GrC 2010), San Jose, Aug 2010.
• J. Ghosh, “Actionable mining of large, multi-relational data using localized predictive models”. Proc. KDIR10, Valencia, Oct 2010, pp. 9-10.
• A. Acharya, E.R. Hruschka and J. Ghosh "Transfer Learning with Cluster Ensembles", JMLR W&CP for ICML 2011, Transfer Learning.
• Aayush Sharma, Meghana Deodhar, and Joydeep Ghosh, “Prediction of New Customer-Product Affinities from Rich Dyadic Data using Localized Models”, Proc. International Workshop on Data Mining in Marketing DMM 2011, Sept 2011.
• O Koyejo and Joydeep Ghosh, "A Kernel-Based Approach to Exploiting Interaction-Networks in Heterogeneous Information Sources for Improved Recommender Systems", in Proc. 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec 2011), Oct 2011, pp. 9-16. ACM.
• Clinton Jones, Joydeep Ghosh and Aayush Sharma, "Learning Multiple Models for Exploiting Predictive  Heterogeneity in Recommender Systems" in Proc. 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec 2011), Oct 2011, pp. 17-24. ACM.
• Yubin Park and Joydeep Ghosh, “A Probabilistic Imputation Framework for Regression Analysis using Variably Aggregated, Multi-source Healthcare Data”, in Proc. IHI 2012 : 2nd ACM SIGHIT International Health Informatics Symposium, Jan 2012.
• A. Kumar, R Chatwin and J Ghosh, “Simple Unsupervised Topic Discovery for Attribute Extraction in SEM Tasks using WordNet”, in Proc. SemRel2012, with LREC 2012, Istanbul, May 2012.
• J. Ho, C Lee and J Ghosh, “Imputation-Enhanced Prediction of Septic Shock in ICU Patients”, in KDD 2012, Health-Informatics Workshop, Beijing, Aug 2012.
• Sreangsu Acharyya, Oluwasanmi Koyejo, Joydeep Ghosh, “Learning to Rank With Bregman Divergences and Monotone Retargeting”, in Proc. UAI 2012, Catalina, Aug 2012, pp. 15-25.
• Joyce C. Ho, Yubin Park, Carlos M. Carvalho and Joydeep Ghosh, “DYNACARE: Dynamic Cardiac Arrest Risk Estimation”, in Proc. AISTATS’13, Apr 2013.
• M. Park, O. Koyejo, J. Ghosh, J. Pillow and R. Poldrack, “Bayesian Structure Learning for Functional Neuroimaging”, in Proc. AISTATS’13, Apr 2013.

· Acharya, Ayan, Hruschka, Eduardo R., Ghosh, Joydeep, Sarwar, Badrul, and Ruvini, Jean-David, “Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning”, in Proc. SDM 2013, May 2013, pp.

· O. Koyejo and J. Ghosh, “A Representation Approach for Relative Entropy Minimization with Expectation Constraints”, in WDDL13, with ICML13, June 2013

• Oluwasanmi Koyejo, Priyank Patel, Joydeep Ghosh and Russell A. Poldrack, “Learning Predictive Cognitive Structure from fMRI using Supervised Topic Models”, in Proc. 3rd International Workshop on Pattern Recognition in NeuroImaging, June 2013,
• C. Lee, O. Koyejo and J. Ghosh,” Identifying candidate disease genes using a trace norm constrained bipartite ranking model”, in Proc. IEEE Engineering in Medicine and Biology Society (EMBC'13), Osaka, Japan, July 2013, pp. 3459-62.
• O. Koyejo and J. Ghosh, "Constrained Bayesian Inference for Low Rank Multitask Learning" in Proc. UAI, July 2013 (Amazon Best Student Paper Award).
• Suriya Gunasekar, Ayan Acharya, Neeraj Gaur, J. Ghosh, “Noisy Matrix Completion Using Alternating Minimization”, Proc. ECML/PKDD, Prague, Sept 2013, pp. 194-209.
• O. Koyejo, S. Archaryya, J. Ghosh, “Retargeted Matrix Factorization for Collaborative Filtering”, in Proc. RecSys, Hong Kong, Oct 2013, pp. 49-56.
• O. Koyejo, C. Lee, J. Ghosh, “Gaussian Process Regression with Functional Expectation Constraints,” in Proc. ICDM 2013 workshop on Biological Data Mining and its Applications in Healthcare (BioDM), Dallas, Dec 2013
• A. Acharya, R. Moooney and J Ghosh, “Multitask Learning with Doubly Supervised Latent Dirichlet Allocation”, in NIPS workshop on Topic Models: Computation, Application, and Evaluation, Dec 2013
• A. Acharya, R. Moooney and J Ghosh, “Active Multitask Learning Using Both Latent and Supervised Shared Topics”, in Proc. SDM 2014, Philadelphia
• Yubin Park, Carlos M. Carvalho and Joydeep Ghosh, “LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series”, in Proc. AISTATS’14, Apr 2014.
• S. Gunasekar, P. Ravikumar and J. Ghosh, “ Exponential Family Matrix Completion under Structural Constraints”, in Proc. ICML’14, June 14,
• S. Acharyya and J. Ghosh, “MEMR: A Margin Equipped Monotone Retargeting Framework for Ranking”, in Proc. UAI 2014, July 2014, pp.

· J. Ho, J. Ghosh and J. Sun, “Marble: High-throughput Phenotyping from Electronic Health Records via Sparse Nonnegative Tensor Factorization”, ”, in Proc. KDD 2014, August 2014, pp.

· Y. Park and J. Ghosh, “LUDIA: An Aggregate-Constrained Low-Rank Reconstruction Algorithm to Leverage Publicly Released Health Data”, in Proc. KDD 2014, August 2014