Arindam Banerjee: Publications

Publications

Online Alternating Directions Method
H. Wang and A. Banerjee.
International Conference on Machine Learning (ICML), 2012.
Gap Filling in the Plant Kingdom---Trait Prediction Using Hierarchical Probabilistic Matrix Factorization
H. Shan, J. Kattge, P. B. Reich, A. Banerjee, F. Schrodt, and M. Reichstein.
International Conference on Machine Learning (ICML), 2012.
MAP Inference on Million Node Graphical Models: KL-divergence based Alternating Directions Method
Qiang Fu, Huahua Wang, Arindam Banerjee, Stefan Liess, and Peter K. Snyder
Technical Report TR-12-007
Department of Computer Science & Engineering, University of Minnesota, Twin Cities, 2012 (pdf).
Online Quadratically Constrained Convex Optimization with Applications to Risk Adjusted Portfolio Selection
Puja Das and Arindam Banerjee
Technical Report TR-12-008
Department of Computer Science & Engineering, University of Minnesota, Twin Cities, 2012 (pdf).
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
T. Zhou, H. Shan, A. Banerjee, and G. Sapiro.
SIAM International Conference on Data Mining (SDM), 2012 (pdf).
Sparse Group Lasso: Consistency and Climate Applications
S. Chatterjee, K. Steinhaeuser, A. Banerjee, S. Chatterjee, and A. Ganguly.
SIAM International Conference on Data Mining (SDM), 2012.
Drought Detection for the Last Century: A MRF-based Approach
Q. Fu, A. Banerjee, S. Liess, and P. Snyder.
SIAM International Conference on Data Mining (SDM), 2012 (pdf).
Emerging Topic Detection using Dictionary Learning
S. Kasiviswanathan, P. Melville, A. Banerjee, and V. Sindhwani.
ACM Conference on Information and Knowledge Management (CIKM), 2011 (pdf).
Efficient Similarity Search for Covariance Matrices via the Jensen-Bregman LogDet Divergence
A. Cherian, S. Sra, A. Banerjee, and N. Papanikolopoulos
International Conference on Computer Vision (ICCV), 2011 (pdf).
Common Component Analysis for Multiple Covariance Matrices
H. Wang, A. Banerjee, and D. Boley.
International Conference on Knowledge Discovery and Data Mining (KDD), 2011 (pdf, longer version).
Meta Optimization and its Application to Portfolio Selection
P. Das and A. Banerjee.
International Conference on Knowledge Discovery and Data Mining (KDD), 2011 (pdf).
Probabilistic Matrix Addition
A. Agovic, A. Banerjee, and S. Chatterjee.
International Conference on Machine Learning (ICML), 2011 (pdf).
Diagnosing Endometrial Carcinoma via Computer-Assisted Image Analysis
R. Sivalingam, G. Somasundaram, A. Ragipindi, A. Banerjee, V. Morellas, N. Papanikolopoulos, and A. Truskinovsky.
Annual Meeting of the United States & Canadian Academy of Pathology (USCAP), 2011.
Mixed-Membership Naive Bayes Models
H. Shan and A. Banerjee.
Data Mining and Knowledge Discovery (DMKD), 23(1), 1-62, 2011.
Bayesian Cluster Ensembles
H. Wang, H. Shan, and A. Banerjee.
Statistical Analysis and Data Mining, 4(1), 54-70, 2011.
Generalized Probabilistic Matrix Factorizations for Collaborative Filtering
H. Shan and A. Banerjee.
IEEE International Conference on Data Mining (ICDM), 2010 (pdf,longer version).
A Generalized Linear Threshold Model for Multiple Cascades
N. Pathak, A. Banerjee, and J. Srivastava.
IEEE International Conference on Data Mining (ICDM), 2010 (pdf).
A related earlier Tech Report.
Anomaly Detection for Discrete Sequences: A Survey
V. Chandola, A. Banerjee, and V. Kumar.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2010 (to appear).
Analyzing aviation safety reports: From topic modeling to scalable multi-label classification
A. Agovic, H. Shan, and A. Banerjee.
Conference on Intelligent Data Understanding (CIDU), 2010 (pdf).
Gaussian Process Topic Models
A. Agovic and A. Banerjee.
Conference on Uncertainty in Artificial Intelligence (UAI), 2010 (pdf).
Keep it Simple with Time: A re-examination of Probabilistic Topic Detection Models
Q. He, K. Chang, E.-P. Lim, and A. Banerjee.
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 32(10), 1795-1808, 2010. (pdf)
Discovering Client and Intervention Patterns in Home Visiting Data
K. Monsen, A. Banerjee, and P. Das.
Western Journal of Nursing Research , 36(4), 2010.
Residual Bayesian Co-clustering for Matrix Approximation
H. Shan and A. Banerjee.
SIAM International Conference on Data Mining (SDM), 2010 (pdf).
Sparsity-cognizant overlapping co-clustering for behavior inference in social networks
H. Zhu, G. Mateos, G. B. Giannakis, N. D. Sidiropoulus, and A. Banerjee
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) , 2010 (pdf).
Discriminative Mixed-membership Models
H. Shan, A. Banerjee, and N. Oza.
IEEE International Conference on Data Mining (ICDM), (2009) (pdf).
Bayesian Overlapping Subspace Clustering
Q. Fu and A. Banerjee.
IEEE International Conference on Data Mining (ICDM), (2009) (pdf).
Approximation Algorithms for Tensor Clustering
S. Jegelka, S. Sra, and A. Banerjee.
The 20th International Conference on Algorithmic Learning Theory (ALT), (2009) (pdf).
Anomaly Detection: A Survey
V. Chandola, A. Banerjee, and V. Kumar.
ACM Computing Surveys, 41(3), Article 15, (2009) (pdf).
Anomaly Detection in Transportation Corridors using Manifold Embedding
A. Agovic, A. Banerjee, A. Ganguly, and V. Protopopescu.
Intelligent Data Analysis, 13(3), 435-455, (2009).
Symmetrized Bregman Divergences and Metrics
A. Banerjee, D. Boley, and S. Acharyya
Snowbird Learning Workshop, (2009).
Bayesian Cluster Ensembles
H. Wang, H. Shan, A. Banerjee.
SIAM International Conference on Data Mining (SDM), (2009) (pdf).
Semi-Supervised Learning of User-Preferred Travel Schedules
A. Agovic, M. Gini, A. Banerjee.
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), (2009).
Use of computerized datasets and data mining methods to predict public health nurse home visiting client outcomes
K. A. Monsen, M. J. Kerr, K. Abe, K. S. Martin, and A. Banerjee.
World Academy of Nursing Science, (2009).
Discovering Effective Models for Home Visiting Practice
K. A. Monsen, A. Banerjee, V. K. Ramadoss, P. Das, and K. Savik.
Midwest Nursing Research Society Annual Meeting, (2009).
Bayesian Co-clustering
H. Shan, A. Banerjee.
IEEE International Conference on Data Mining (ICDM), (2008) (pdf).
Multiplicative Mixture Models for Overlapping Clustering
Q. Fu, A. Banerjee.
IEEE International Conference on Data Mining (ICDM), (2008) (pdf).
A Social Query Model for Distributed Search
A. Banerjee, S. Basu.
2nd ACM Workshop on Social Network Mining and Analysis (SNAKDD), (2008) (pdf).
Social Topic Models for Community Extraction
N. Pathak, C. DeLong, K. Erickson, A. Banerjee.
2nd ACM Workshop on Social Network Mining and Analysis (SNAKDD), (2008) (pdf).
Clustering with Balancing Constraints
A. Banerjee, J. Ghosh.
Constrained Clustering: Advances in Algorithms, Theory, and Applications, CRC Press, (2008).
Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection
J. Wan, S. Kang, C. Tang, J. Yan, Y. Ren, J. Liu, X. Gao, A. Banerjee, L. Ellis, T. Li.
Nucleic Acids Research (NAR), (2008).
I/O Scalable Bregman Clustering
K. Hsu, A. Banerjee, J. Srivastava.
Pacific-Asian Conference on Knowledge Discovery and Data Mining (PAKDD), (2008).
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
A. Banerjee, I. Dhillon, J. Ghosh, S. Merugu, D. Modha.
Journal of Machine Learning Research (JMLR), (2007), (pdf).
Latent Dirichlet Conditional Naive Bayes Models
A. Banerjee and H. Shan.
IEEE International Conference on Data Mining (ICDM) (2007) (pdf).
Anomaly Detection in Transportation Corridors using Manifold Embedding
A. Agovic, A. Banerjee, A. Ganguly, and V. Protopopescu.
1st International Workshop on Knowledge Discovery from Sensor Data (Sensor-KDD) (2007).
An Analysis of Logistic Models: Exponential Family Connections and Online Performance
A. Banerjee.
SIAM International Conference on Data Mining (SDM) (2007) (pdf).
Multi-way Clustering on Relation Graphs
A. Banerjee, S. Basu, S. Merugu.
SIAM International Conference on Data Mining (SDM) (2007) (pdf).
Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
A. Banerjee, S. Basu.
SIAM International Conference on Data Mining (SDM) (2007) (pdf, Longer version).
On Bayesian Bounds
A. Banerjee.
International Conference on Machine Learning (ICML) (2006) (pdf).
Scalable Clustering with Balancing Constraints
A. Banerjee and J. Ghosh.
Data Mining and Knowledge Discovery (2006) (pdf).
Probabilistic Semi-supervised Clustering with Constraints
S. Basu, M. Bilenko, A. Banerjee, and R. Mooney
Semi-Supervised Learning MIT Press, (2006).
A Clustering Based Approach to Perceptual Image Hashing
V. Monga, A. Banerjee and B. Evans.
IEEE Transactions on Information Forensics and Security (2006).
Model Based Overlapping Clustering
A. Banerjee, C. Krumpelman, S. Basu, R. Mooney and J. Ghosh.
International Conference on Knowledge Discovery and Data Mining (KDD) (2005) (ps,pdf).
Clustering with Bregman Divergences
A. Banerjee, S. Merugu, I. Dhillon and J. Ghosh.
Journal of Machine Learning Research (JMLR) (2005) (pdf).
Clustering on the Unit Hypersphere using Von Mises-Fisher Distributions
A. Banerjee, I. Dhillon, J. Ghosh and S. Sra.
Journal of Machine Learning Research (JMLR) (2005) (pdf).
On the Optimality of Conditional Expectation as a Bregman Predictor
A. Banerjee, X. Guo and H. Wang.
IEEE Transactions on Information Theory, 51(7), 2664-2669 (2005) (pdf).
An Objective Evaluation Crietrion for Clustering
A. Banerjee and J. Langford.
International Conference on Knowledge Discovery and Data Mining (KDD) (2004) (ps).
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
A. Banerjee, I. Dhillon, J. Ghosh, S. Merugu, D. Modha.
International Conference on Knowledge Discovery and Data Mining (KDD) (2004).
An Information Theoretic Analysis of Maximum Likelihood Mixture Estimation for Exponential Families
A. Banerjee, I. Dhillon, J. Ghosh and S. Merugu.
International Conference on Machine Learning (ICML) (2004). (ps).
Frequency Sensitive Competitive Learning for Balanced Clustering on High-dimensional Hyperspheres
A. Banerjee, and J. Ghosh.
IEEE Transactions on Neural Networks (2004) (ps).
Rate Distortion, Bregman Divergences and Maximum Likelihood Mixture Estimation
A. Banerjee, I. Dhillon, J. Ghosh and S. Merugu.
The Learning Workshop at Snowbird (2004).
Optimal Bregman Prediction and Jensen's Equality
A. Banerjee, X. Guo and H. Wang.
IEEE International Symposium on Information Theory (ISIT) (2004) (pdf).
Clustering with Bregman Divergences
A. Banerjee, S. Merugu, I. Dhillon and J. Ghosh.
SIAM International Conference on Data Mining (SDM) (2004) (ps, pdf).
Active Semi-supervision for Pairwise Constrained Clustering
S. Basu, A. Banerjee and R. Mooney.
SIAM International Conference on Data Mining (SDM) (2004) (pdf).
Mean Model Clustering
A. Banerjee, and J. Ghosh. The Learning Workshop at Snowbird (2003) (ps).
Generative Model-based Clustering of Directional Data
A. Banerjee, I. Dhillon, J. Ghosh and S. Sra.
International Conference on Knowledge Discovery and Data Mining (KDD) (2003) (pdf).
Competitive Learning Mechanisms for Scalable, Incremental and Balanced Clustering of Streaming Texts
A. Banerjee, and J. Ghosh.
International Joint Conference on Neural Networks(IJCNN): Special Session on Incremental Learning (2003).
Semi-supervised Clustering by Seeding
S. Basu, A. Banerjee, and R. Mooney.
Proceedings of the International Conference on Machine Learning (ICML) (2002) (ps, pdf).
On Scaling Up Balanced Clustering Algorithms
A. Banerjee, and J. Ghosh.
Proceedings of the 2nd SIAM International Conference on Data Mining (SDM) (2002) (ps, pdf).
Frequency Sensitive Competitive Learning for Clustering on High Dimensional Hyperspheres
A. Banerjee, and J. Ghosh.
Proceedings of the International Joint Conference on Neural Networks (IJCNN) (2002) (ps, pdf).
Characterizing Visitors to a Website Across Multiple Sessions
A. Banerjee and J. Ghosh.
Proceedings of the National Science Foundation(NSF) Workshop on Next Generation Data Mining (2002).
Clickstream Clustering using Weighted Longest Common Subsequence
A. Banerjee, and J. Ghosh.
Proceedings of the 1st SIAM International Conference on Data Mining: Workshop on Web Mining (2001) (ps, pdf).
Concept-based Clustering of Clickstream Data
A. Banerjee, and J. Ghosh.
Proceedings of the 3rd International Conference on Information Technology, pp 145-160 (2000).
Computerized Tumor Boundary Detection Using Genetic Algorithm
A. Banerjee.
Proceedings of the National Conference on Applications of Signal Processing, India (1998).