Anitha Kannan
RESEARCHER
.
I am a researcher at Microsoft Research Search Labs.
My research focuses on applications of machine learning to search. I am also interested in problems arising in computer vision and computational biology.
Previously, I spent two years at MSR Cambridge in the Machine learning and perception group.During 2007-08, I was also a Fellow of the Darwin College, University of Cambridge. I did my PhD at University of Toronto where I was a member of Brendan Frey’s Probabilistic and Statistical Inference group.
Publications
- Rakesh Agrawal, Sunandan Chakraborty, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi, Empowering Authors to Diagnose Comprehension Burden in Textbooks, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), ACM, August 2012
- Yi Yang, Simon Baker, Anitha Kannan, and Deva Ramanan, Recognizing Proxemics in Personal Photos, in IEEE Conference on Computer Vision and Pattern Recognition , June 2012
- Thomas Lin, Patrick Pantel, Michael Gamon, Anitha Kannan, and Ariel Fuxman, Active Objects: Actions for Entity-Centric Search, in World Wide Web, ACM, April 2012
- Rakesh Agrawal, Sunandan Chakraborty, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi, Quality of Textbooks: An Empirical Study, in ACM DEV, ACM, March 2012
- Anitha Kannan, Partha Pratim Talukdar, Nikhil Rasiwasia, and Qifa Ke, Improving Product Classification Using Images, in International Conference on Data Mining, IEEE, December 2011
- Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi, Data Mining for Improving Textbooks, in SIGKDD Explorations Newsletter, ACM, December 2011
- Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi, Enriching Textbooks with Images, in Proc. Conference on Information and Knowledge Management, ACM, October 2011
- Anitha Kannan, Inmar Givoni, Rakesh Agrawal, and Ariel Fuxman, Matching Unstructured Offers to Structured Product Descriptions, in International Conference on Knowledge Discovery and Data Mining (KDD), ACM, August 2011
- Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi, Enriching Education through Data Mining, in International Conference on Pattern Recognition and Machine Intelligence (PReMI), LNCS 6744, Springer Verlag, June 2011
- Ekaterina Gonina, Anitha Kannan, John Shafer, and Mihai Budiu, Parallelizing large-scale data processing applications with data skew: a case study in product-offer matching, in International Workshop on MapReduce and its Applications (MapReduce) 2011, June 2011
- Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi, Identifying Enrichment Candidates in Textbooks, in International World Wide Web Conference, ACM, March 2011
- Anitha Kannan, Inmar E.Givoni, Rakesh Agrawal, and Ariel Fuxman, Matching Unstructured Product Offers to Structured Product Descriptions, no. MSR-TR-2010-172, 1 August 2010
- Ariel Fuxman, Anitha Kannan, Andrew B Goldberg, Rakesh Agrawal, Panayiotis Tsaparas, and John Shafer, Improving Classification Accuracy Using Automatically Extracted Training Data, in International Conference on Knowledge Discovery and Data Mining, June 2009
- Fan Guo, Chao Liu, Anitha Kannan, Tom Minka, Michael Taylor, Yi-Min Wang, and Christos Faloutsos, Click Chain Model in Web Search, in WWW'09: Proceedings of the 18th International World Wide Web Conference, Association for Computing Machinery, Inc., April 2009
- Kai Ni, Anitha Kannan, Antonio Criminisi, and John Winn, Epitomic Location Recognition, in IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI special issue), IEEE, 2009
- Oliver Stegle, Anitha Kannan, Richard Durbin, and John M. Winn, Accounting for Non-genetic Factors Improves the Power of eQTL Studies, in International Conference on Research in Computational Molecular Biology, 2008
- Kai Ni, Anitha Kannan, Antonio Criminisi, and John Winn, Epitomic Location Recognition, in Proc IEEE Conference on Computer Vision (CVPR). Winner of BEST STUDENT PAPER RUNNER UP AWARD., IEEE Computer Society, 2008
- Thomas Kislinger, Brian Cox, D.A. Wigle, Anitha Kannan, K. Brown, T. Okubo, B. Hogan, I. Jurisica, B.J. Frey, J. Rossant, and A. Emili, Integrated proteomic and transcriptomic profiling of mouse lung development and Nmyc target genes, in Molecular Systems Biology, pp. 173–86, 2007
- Anitha Kannan, John Winn, and Carsten Rother, Clustering appearance and shape by learning jigsaws, in Advances in Neural Information Processing Systems, MIT Press, 2007
- Anitha Kannan, Andrew Emili, and Brendan J. Frey, A Bayesian Model That Links Microarray mRNA Measurements to Mass Spectrometry Protein Measurements, in International Conference on Research in Computational Molecular Biology, 2007
- Jim C. Huang, Anitha Kannan, and John M. Winn, Bayesian association of haplotypes and non-genetic factors to regulatory and phenotypic variation in human populations, in International Conference on Intelligent Systems for Molecular Biology, 2007
- Julia Lasserre, Anitha Kannan, and John Winn, Hybrid learning of large jigsaws, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007
- Thomas Kislinger, Brian Cox, Anitha Kannan, C. Chung, A. Ignatchenko, M.S. Scott, A. Gramolini, Q. Morris, T. Hughes, J. Rossant, B.J. Frey, and A. Emili, Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling, in Cell, pp. 173–86, 2006
- Anitha Kannan, John Winn, and Carsten Rother, Clustering appearance and shape by learning jigsaws, in NIPS, 2006
- Anitha Kannan, Brendan J. Frey, and Nebojsa Jojic, A generative model for dense optical flow in layers, in In Workshop on Spatial Coherence for Visual Motion Analysis, 2004
- Anitha Kannan, Nebojsa Jojic, and Brendan Frey, Fast transformation-invariant factor analysis, in In Advances in Neural Information Processing Systems, MIT Press, 2003
- Nebojsa Jojic, Brendan J. Frey, and Anitha Kannan, Epitomic analysis of appearance and shape, in In ICCV, 2003
- Brendan J. Frey, Nebojsa Jojic, and Anitha Kannan, Learning appearance and transparency manifolds of occluded objects in layers, in In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003
- Brendan Frey, Anitha Kannan, and Nebojsa Jojic, Product analysis - Learning observations as products of hidden variables, in In Advances in Neural Information Processing Systems, MIT Press, 2002
- Brendan Frey and Anitha Kannan, Accumulator networks: Suitors of local probability propagation, in In Advances in Neural Information Processing Systems, MIT Press, 2001
