Source: https://drona.csa.iisc.ac.in/~mnm/
Timestamp: 2019-04-24 04:21:41+00:00

Document:
T. R. babu, M. N. Murty nd S. V. Subrahmanya, Compresion Schemes for Mining Large Datasets: A Machine Learning Perspective, Springer, 2013.
M. N. Murty and V. Susheela Devi, Introduction to Pattern Recognition and Machine Learning, IISc Lecture Notes Series, World Scientific, 2015.
M. N. Murty and R. Raghava, Support Vector Machines and Perceptrons: Learning, Optimization and Application to Social Networks, Springer Briefs in Computer Science, 2016.
M. N. Murty and A. Negi, A Knowledge-Based Approach to Cluster Analysis, in Systems and Signal Processing, pp. 747-755, edited by R. N. Madan, N. Viswanadham, and R. L. Kashyap, Oxford and IBH Publishing Company, New Delhi, 1991.
V. Sridhar and M. N. Murty, Knowledge Processing Under Uncertainty, in Knowledge Based Systems, pp. 157-189, edited by S. G. Tzafestas, World Scientific, London, 1997.
V. Susheela Devi and M. N. Murty, Handwritten Digit Recognition Using Soft Computing, in Soft-Computing for Image Processing, pp. 506-524, edited by S. K. Pal, A. Ghosh and M. K. Kundu, Physica-Verlag, Heidelberg, 2000.
Andreas Moser and M. N. Murty, On the scalability of Genetic Algorithms to very large-scale feature selection, in Real-World Applications of Evoltionary Computing, pp. 309-31, edited by Stefano Cagnoni, Springer, LNCS: Vol. 1803, 2000.
M. N. Murty, Clustering Large Data Sets, in Soft Computing Approach to Pattern Recognition and Image Processing, pp. 41-63, edited by A. Ghosh and S. K. Pal, World-Scientific, New Jersey, 2002.
E. Diday and M. N. Murty, Symbolic Data Clustering, in Encyclopedia of Data Warehousing and Mining, pp. 1087-1092, Edited by J. Wang, Idea Group Inc., 2005.
P. Viswanath, M. N. Murty, and S. Bhatnagar, Pattern Synthesis for Large-Scale Pattern Classification, In Encyclopedia of Data Warehousing and Mining, pp. 902-906, Edited by. J. Wang, Idea Group Inc., 2005.
M. N. Murty, B. Rashmin and C. Bhattacharyya, Clustering based on Genetic Algorithms, In Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases, pp. 137-159, Edited by Ashish Ghosh, Satchidananda Dehuri, and Susmita Ghosh, Springer, 2008.
E. Thirumaran and M. N. Murty, Collaborative Filtering Based Recommendation Systems, in Text and Web Mining Technologies, Edited by M. Song and Y-F Brook Wu, 2009.
V. Suresh Babu, P. Viswanath and M. N. Murty, Non-Parametric Methods for Large Datasets, In Encyclopedia of Data Warehousing and Mining, pp. 1708-1713, Edited by. J. Wang, Idea Group Inc., 2009.
N. Ranga Suri, M. N. Murty and G. Athithan, Data Mining Techniques for Outlier Detection, in Visual Analytics and Interactive Technologies: Data, Text and Web Mining Applications, pp. 19-38, Edited by Q. Zhang, R. Segall, and M. Cao, IGI Global, 2011.
T. Ravindra Babu, M. N. Murty, and S. V. Subrahmanya, Quantization based Sequence Generation and Subsequence Pruning for Data Mining Applications, in Pattern Discovery Using Sequence Data Mining: Applications and Studies, pp. 94-110, Edited by Pradeep Kumar, P. Radha Krishna and S. Bapi Raju, 2012.
B. Shekar, M. N. Murty, and G. Krishna, Pattern clustering: an artificial intelligence approach, Proceedings of the 10th International Joint Conference on Artificial Intelligence, Milano, Italy, Aug. 1987.
V. Sridhar, M. N. Murty, and G. Krishna, A logical model for decision-making, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Dec. 1989.
S. H. Srinivasan and M. N. Murty, Validation in distributed representation, in International Joint Conference on Neural Networks, Singapore, pp. 36-42, November 1991.
G. P. Babu and M. N. Murty, Probabilistic connectionist approaches for the design of good communication codes, In the Proc. of the IJCNN, Japan, 1993.
G. P. Babu and M. N. Murty, Controlled offspring generation in evolutionary programming, in Proc. of the Third Annual Conf. on Evolutionary Programming, San Diego, 1994.
S. V. N. Vishwanathan and M. N. Murty, Geometric SVM: a fast and intuitive SVM algorithm. In Proc. Intl. Conf. Pattern Recognition, Vol. 2, pp. 56-59, 2002.
D. Ambedkar, M. N. Murty, and S. Bhatnagar, Quotient evolutionary space: abstraction of evolutionary process w.r.t macroscopic properties, In Proceedings of IEEE Congress on Evolutionary Computation, 2003.
D. Ambedkar, M. N. Murty, and S. Bhatnagar, Cauchy annealing schedule: an annealing schedule for Boltzmann selection scheme in evolutionary algorithms, In Proceedings of IEEE Congress on Evolutionary Computation (CEC'2004), 2004.
P. A. Vijaya, M. N. Murty, and D. K. Subramanian, An efficient technique for protein sequence clustering and classification, In Proc. of 17th ICPR (Int. Conf. in Pattern Recognition), Vol. 2, pp. 447-450, 2004.
P. Viswanath, M. N. Murty, and S. Bhatnagar, A pattern synthesis technique with an efficient nearest neighbor classifier for binary pattern recognition, In Proceedings of International Conference on Pattern Recognition (ICPR), Vol. 4, pp. 416-419, 2004.
D. Dipti, M. Vidyasagar, and M. N. Murty, Bimodal projection-based features for pattern classification, In Proceedings of the IJCNN at the IEEE world Congress on Computational Intelligence, 2006.
S. Asharaf, S. K. Shevade, and M. N. Murty, Scalable non-linear support vector machine using hierarchical clustering, ICPR Vol. 1, pp. 908-911, 2006.
S. Asharaf, M. N. Murty, and S. K. Shevade, Cluster based core vector machine, In Proceedings of Intl. Conf. on Data Mining, 2006.
S. Asharaf, M. N. Murty, and S. K. Shevade, Multiclass Core Vector Machine, in the Proceedings of the 24th ICML, June 2007.
B. Rashmin, J. Saketha Nath, K. Suresh Kumar, K. Sivaramakrishnan, C. Bhattacharyya, and M. N. Murty, Focussed Crawling with Scalable Ordinal regression solvers, in the Proceedings of the 24th ICML, June 2007.
A. P. Yogananda, M. N. Murty, and Lakshmi Gopal, A fast linear separability test by projection of positive points on subspaces, in the Proceedings of the 24th ICML, June 2007.
R. Arun, V. Suresh, R. Saradha, M. N. Murty, and C. E. Veni Madhavan, Stopwords and Stylometry : A Latent Dirichlet Allocation Approach, In NIPS Workshop on Applications for Topic Models: Text and Beyond, 2009.
Ambedkar Dukkipati, Abhay Kumar Yadav, and M. N. Murty, Maximum entropy model based classification with feature selection, ICPR 2010.
Geetha Manjunath, M. N. Murty, and Dinkar Sitaram, A Practical Heterogeneous Classifier for Relational Databases, ICPR 2010.
R. Arun, V. Suresh, C. E. Veni Madhavan, M. N. Murty: On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations, PAKDD 2010.
Govind Sharma and M. Narasimha Murty, Mining Sentiments from Songs Using Latent Dirichlet Allocation, IDA 2011.
Arghya Roy Chaudhuri and M. Narasimha Murty, On the relation between K-means and PLSA, ICPR 2012.
Deepak Gujraniya, M. Narsimha Murty: Efficient classification using phrases generated by topic models. ICPR 2012.
B. Shekar: A Knowledge-Based Approach to Pattern Clustering, 1988 (with Prof. G. Krishna).
S.H. Srinivasan: Studies in Learning and Representation in connectionist Networks, 1993.
V. Sridhar: Labelled clustering and its Applications, 1993.
G. Phanendra Babu: Evolutionary and Connectionist Approaches to Pattern Clustering, 1994 (with Prof. S. Sathiya Keerthi).
M. Prakash: Learning in Subspace Methods Using weighted and Multi-Subspace Representations, 1996.
S. Bhattacharya: A Novel Scheme for Speech Synthesis, 1997.
V. Susheela Devi: Optimal Prototype Selection for Efficient Pattern Classification, 2001 (with Prof. Indraneel Sen).
K. R. K. Murthy: Sharable Instructable Agent for Information Filtering, 2001 (with Prof. S. Sathiya Keerthi).
C. Bhattacharyya: Plefka's Mean-Field Theory and Belief Networks, 2002 (with Prof. Sathiya Keerthi).
S. K. Shevade: Some Efficient Algorithms for Support Vector Machines, 2001 (with Prof. S. Sathiya Keerthi).
Dipti Deodhare: Bimodal Projections Based Features for High Dimensional Pattern Classification, 2001 (with Dr. M. Vidyasagar).
V. S. Ananthanarayana: Knowledge-Based Mining of Multi-Databases for Associations, 2001 (with Prof. D. K. Subramanian).
S. V. N. Vishwanathan: Kernel Methods: Fast Algorithms and Real Life Applications, 2003.
P. Viswanath: Pattern Synthesis Techniques and Compact Data Representation Schemes for Efficient Nearest Neighbor Classification, 2005 (with Dr. S. Bhatnagar) (Awarded the Best Thesis Award).
P. A. Vijaya: Efficient Hierarchical Clustering Techniques for Pattern Classification, 2005 (with Prof. D. K. Subramanian).
D. Ambedkar: On generalized Measures of Information with Maximum and Minimum Entropy Prescriptions, 2006(with Dr. S. Bhatnagar).
T. Ravindra Babu: Efficient Schemes for Large-Scale Pattern Classification, 2006 (with Dr. V. K. Agrawal).
S. Asharaf: Efficient Kernel Methods for Large Scale Classification, 2007 (with Dr. S. K. Shevade)(IBM Outstanding PhD student award).
Geetha Manjunath, Semantic Analysis of Web Pages for Task-Based Personal Web Interactions, 2013 (with Dr. Dinkar Sitaram, HP Research Labs, Bangalore).
N. N. Ranga Suri, Outlier Detection with Applications in Graph Data Mining, 2014 (with Dr. Athithan, CAIR, Bangalore).
Shyni Thomas, Planning based on Informed Search (In Progress) (with Dr. Dipti Deodhare, CAIR, Bangalore).
Govind Sharma, Document Summarization(In Progress).
Sharad Nandanawar, Topic Models(In Progress).
C. Srinivas: Pattern classification using conjunctive conceptual clustering procedures, 1986.
S. Choudhury: Hierarchical Data Structures for Pattern Recognition, 1987.
Malini K. Bhandaru: Learning from examples using Hierarchical Counterfactual Expressions, 1989.
Atul Negi: Algorithmic knowledge for a knowledge-based clustering environment, 1989.
V. Rajasekar: Intelligent Backtracking in Logic Programs, 1990.
V.S.S. Suresh Babu: Preprocessing for Optimal Multilevel clustering, 1990.
Francis Joy: Reason Maintenance and Logic, 1993.
V. Vijaya Saradhi: Pattern Representation and Prototype Selection for Handwritten Digit Recognition, 1999.
P. Ramanujam: Development of a General-Purpose Sanskrit Parser, 1999 (with Prof. Nagaraj Shenoy).
T. Ravindra Babu: Data Clustering and Evolutionary Algorithms for Data Mining, 2000 (with Dr. M. Sambasiva Rao).
D. Ambedkar: ACE-Model: A Conceptual Evolutionary Model for Evolutionary Computation and Artificial Life, 2002.
B. N. Ranganath: Efficient Frequent Closed Itemset Algorithms with Applications to Stream Mining and Classification, 2009.
Govind Sharma: Sentiment-Driven Topic Analysis of Song Lyrics, 2012.
The paper "Pattern Clustering: A Review" coauthored by him is the most frequently downloaded article during 2004, 2005, and 2006 from ACM publications (Source: Communications of the ACM).
Alumni Award for Excellence in Research for Engineering, IISc, Bangalore, 2007.
Fellow, Indian National Academy of Engineering (INAE), India, 2008.
IISc Colloquium, "Clustering Large Data sets", delivered on March 29, 2010.
Associate Editor, Sadhana, An Official Journal of the Indian Academy of Sciences, published by Springer.
Fellow, The National Academy of Sciences (NASI), India, 2011.

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