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Aggarwal, M and Murty, MN (2020) Node Representations. [Book Chapter]
Bandyopadhyay, S and Aggarwal, M and Murty, MN (2021) A Deep Hybrid Pooling Architecture for Graph Classification with Hierarchical Attention. In: 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 11-14 May 2021, pp. 554-565.
Vijaikumar, M and Shevade, S and Murty, MN (2021) GRAM-SMOT: Top-N Personalized Bundle Recommendation via Graph Attention Mechanism and Submodular Optimization. In: European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, 14-18 Sep 2020, pp. 297-313.
Vijaikumar, M and Shevade, S and Murty, MN (2021) Neural Cross-Domain Collaborative Filtering with Shared Entities. In: European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, 14-18 Sep 2020, pp. 729-745.
Bandyopadhyay, S and Vishal Vivek, S and Murty, MN (2020) Integrating network embedding and community outlier detection via multiclass graph description. In: Frontiers in Artificial Intelligence and Applications, 29 August-8 September 2020, Santiago de Compostela, Online; Spain, pp. 976-983.
Bandyopadhyay, S and Biswas, A and Kara, H and Murty, MN (2020) A multilayered informative randomwalk for attributed social network embedding. In: Frontiers in Artificial Intelligence and Applications, 29 August-8 September 2020, Santiago de Compostela, Online; Spain, pp. 1738-1745.
Bandyopadhyay, S and Lokesh, N and Vivek, SV and Murty, MN (2020) Outlier resistant unsupervised deep architectures for attributed network embedding. In: WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining, 3-7 Feb., 2020, Houston, USA, pp. 25-33.
Patil, P and Sharma, G and Murty, MN (2020) Negative Sampling for Hyperlink Prediction in Networks. In: 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, 11-14 May 2020, Singapore; Singapore, pp. 607-619.
Aggarwal, M and Murty, MN (2020) Region and relations based multi attention network for graph classification. In: 25th International Conference on Pattern Recognition, 10-15 jan 2021, Virtual, pp. 8101-8108.
Vijaikumar, M and Shevade, S and Murty, MN (2020) SoRecGAT: Leveraging Graph Attention Mechanism for Top-N Social Recommendation. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2019, 16-20 September 2019, Wurzburg; Germany, pp. 430-446.
Vijaikumar, M and Shevade, S and Murty, MN (2019) TagEmbedSVD: Leveraging Tag Embeddings for Cross-Domain Collaborative Filtering. In: 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, 17 - 20 December 2019, Tezpur, pp. 240-248.
Bandyopadhyay, S and Lokesh, N and Murty, MN (2019) Outlier aware network embedding for attributed networks. In: 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, 27 - 1 February 2019, Honolulu, pp. 12-19.
Nandanwar, S and Murty, MN (2018) Overlap-robust decision boundary learning for within-network classification. In: 32nd AAAI Conference on Artificial Intelligence, AAAI 2018, 2 - 7 February 2018, New Orleans, pp. 3844-3851.
Athithan, Biswajit Paul G and Murty, MN (2009) Speeding up AdaBoost Classifier with Random Projection. In: 7th International Conference on Advances in Pattern Recognition, FEB 04-06, 2009, Indian Statist Inst, Kolkata, INDIA,.
Garg, Vikas K and Murty, MN (2009) RACK: RApid Clustering using K-means algorithm. In: IEEE International Conference on Automation Science and Engineering. CASE 2009, AUG 22-25, 2009, Bangalore, pp. 621-626.
Babaria, Rashmin and Saketha Nath, J and Krishnan, S and Sivaramakrishnan, KR and Bhattacharyya, Chiranjib and Murty, MN (2007) Focussed Crawling with large scale Ordinal Regression Solvers. In: ICML '07 Proceedings of the 24th international conference on Machine learning , New York, NY.
Nath, Saketha J and Bhattacharyya, C and Murty, MN (2006) Clustering Based Large Margin Classification: A Scalable Approach using SOCP Formulation. In: KDD '06 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining , 2006, New York, NY.
Babu, TR and Murty, MN and Agrawal, VK (2005) Hybrid learning scheme for data mining applications. In: Hybrid learning scheme for data mining applications, DEC 05-08, 2004, Kitakyushu.
Ananthanarayana, VS and Subramanian, DK and Murty, MN (2003) Association rule mining activity : A general formalism. In: International Conference on Computer, Communication and Control Technologies (CCCT 03)/9th International Conference on Information Systems Analysis and Synthesis (ISAS03), JUL 31-AUG 02, 2003, Orlando, FLORIDA.
Murthy, KRK and Murty, MN and Keerthi, SS (2001) A sharable instructable agent for information filtering. In: International Conference on Computing and Information Technologies, OCT 12, 2001, Montclair, NJ.
Murty, MN and Jain, AK (1996) Knowledge-based clustering. In: International Conference on Ordinal and Symbolic Data Analysis (OSDA 95), JUN 20-23, 1995, PARIS, FRANCE.
Babu, GP and Murty, MN (1994) Connectionist approach for global optimization. In: 1994 IEEE International Conference on Neural Networks (ICNN 94) - 1st IEEE World Congress on Computational Intelligence, JUN 26-29, 1994, ORLANDO, FL.
Babu, GP and Murty, MN (1994) Controlled offspring generation in evolutionary programming. In: Third Annual Conference on Evolutionary Programming, 24-26 Feb. 1994, San Diego, CA, USA, pp. 253-260.
Meher, Saroj K and Murty, MN (2013) Efficient method of moving shadow detection and vehicle classification. In: AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 67 (8). pp. 665-670.
Reddy, Sathish I and Shevade, Shirish and Murty, MN (2011) A fast quasi-Newton method for semi-supervised SVM. In: Pattern Recognition, 44 (10-11,). pp. 2305-2313.
Dukkipati, A and Bhatnagar, S and Murty, MN (2007) Gelfand-Yaglom-Perez theorem for generalized relative entropy functionals. In: Information Sciences, 177 (24). pp. 5707-5714.
Ananthanarayanan, VS and Murty, MN and Subramanian, DK (2001) An incremental data mining algorithm for compact realization of prototypes. In: Pattern Recognition, 34 (11). pp. 2249-2251.
Murthy, KRK and Keerthi, SS and Murty, MN (2001) Rule prepending and post-pruning approach to incremental learning of decision lists. In: Pattern Recognition, 34 (8). pp. 1697-1699.
Jain, AK and Murty, MN and Flynn, PJ (1999) Data Clustering: A Review. In: ACM Computing Surveys, 31 (3). pp. 264-323.
Babu, GP and Murty, MN and Ram, BR (1996) Clan-based evolutionary approach for solving control problems. In: Computers & Mathematics with Applications, 31 (6). pp. 41-60.
Sridhar, V and Murty, MN (1994) A deductive clustering approach. In: Journal of Experimental and Theoretical Artificial Intelligence, 6 (2). pp. 195-237.
Babu, GP and Murty, MN (1994) Simulated annealing for selecting optimal initial seeds in the K-means algorithm. In: Indian Journal of Pure and Applied Mathematics, 25 (1-2). pp. 85-94.
Srivastava, Anurag and Murty, MN (1990) A comparison between conceptual clustering and conventional clustering. In: Pattern Recognition, 23 (9). pp. 975-981.
