Publications

2023 

• Search Behavior Prediction: A Hypergraph Perspective. Y. Han, E. W. Huang, W. Zheng, N. Rao, Z. Wang, K. Subbian, WSDM 2023. [PDF]

• ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding. Z. Liu, G. Hiranandani, K. Qian, E. W. Huang, Y. Xu, B. Zeng, K. Subbian, S. Wang, CIKM 2023. pp 1523-1533. [PDF]

2022

• [NEW DATASET] Shopping Queries Dataset: A Large-scale ESCI Benchmark for Improving Product Search. C. K. Reddy, L. Marquez, F. Valero, N. Rao, H. Zaragoza, S. Bandyopadhyay, A. Biswas, A. Xing, K. Subbian. CoRR abs/2206.06588 2022. 

• Self-supervised Short-test Modeling through Auxiliary Context Generation. N. Choudhary, C. Aggarwal, K. Subbian, C. K. Reddy. ACM Transactions of Intelligent Systems Technology 13(3): 51, pp 1-21, 2022. [PDF]

• Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods. W. Zheng, E. W. Huang, N. Rao, S. Katariya, Z. Wang, K. Subbian. ICLR 2022. [PDF]

• Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance. N. Choudhary, N. Rao, K. Subbian, C. Reddy. KDD 2022. [PDF]

• Learning Backward Compatible Embeddings. W. Hu, R. Bansal, K. Cao, N. Rao, K. Subbian, J. Leskovec. KDD 2022. [PDF]

• AutoGDA: Automated Graph Data Augmentation for Node Classification. T. Zhao, X. Tang, D. Zhang, H. Jiang, N. Rao, Y. Song, P. Agrawal, K. Subbian, B. Yin, M. Jiang. LoG 2022. [PDF]

• ANTHEM: Attentive Hyperbolic Entity Model for Product Search. N. Choudhary, N. Rao, S. Katariya, K. Subbian, C. Reddy, WSDM 2022: 161-171. [PDF]

• Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment. Z. Huang, A. Li, H. Jiang, T. Cao, H. Lu, B. Yin, K. Subbian, Y. Sun, and W. Wang. ACL 2022: 474-485 [PDF]

• ALLIE: Active Learning on Large-scale Imbalanced Graphs. L. Cui, X. Tang, S. Katariya, N. Rao, P. Agrawal, K. Subbian, D. Lee. WWW 2022: 690-698 [PDF]

• [Tutorial] Hyperbolic Networks: Theory, Architectures, and Applications. N. Choudhary, N. Rao, K. Subbian, S. Sengamedu, C. K. Reddy. WWW and KDD 2022. [Tutorial Link] [Teaser Video] 

2021 

• Bipartite Dynamic Representation for abuse detection, A. Wang, R. Ying, P. Li, N. Rao, K. Subbian, J. Leskovec. KDD 2021. [PDF]

• Finding Needles in Heterogeneous Haystacks. B. Adhikari, L. Li, N. Rao, K. Subbian. AAAI 2021: 15232-15239 [PDF]

• Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs. N. Choudhary, N. Rao, S. Katariya, K. Subbian, C. K. Reddy. WWW 2021: 1373-1384 [PDF]

2020

• Regularized Graph Convolutional Networks for Short Text Classification. K. Tayal, N. S. Rao, S. Agarwal, X. Jia, K. Subbian, V. Kumar, In COLING, 2020. [PDF]

• Learning Robust Models for e-Commerce Product Search, T. Ngyuen, N. Rao, and K. Subbian. In ACL, 2020. [PDF]

• Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms. A. Ahuja, N. Rao, S. Katariya, C. Reddy, K. Subbian, WSDM, 2020. [PDF]

• Scalable Feature Selection for (MultiTask) Gradient Boosted Trees. C. Han, N. Rao, D. Sorokina, K. Subbian. in AISTATS, 2020. [PDF]

2019

• Identifying Facet Mismatches In Search Via Micrographs. S. Srinivasan, N. S. Rao, K. Subbian, L. Getoor, in CIKM, Beijing, China, Nov 3-7, 2019. [PDF]

• Online Bayesian Learning for E-Commerce Query Reformulation. G. Hiranandani, S. Katariya, N. Rao, K. Subbian. in NeurIPS workshop, 2019. [PDF]

• Short Text Classification Using Graph Convolutional Network. K. Tayal , N. Rao, S. Agrawal, K. Subbian. In NeurIPS workshop, 2019. [PDF]

2018

• Learning Diffusion using Hyperparameters, D. Kalimeris, Y. Singer, K. Subbian, U. Weinsberg, in ICML, Stockholm, Sweden, Jul 10-15, 2018. [PDF] 

• Do Diffusion Protocols Govern Cascade Growth? J. Cheng, J. Kleinberg, J. Leskovec, D. Liben-Nowell, B. State, K. Subbian, L. Adamic. In ICWSM, Stanford, California. Jun 25-28, 2018. [PDF]

2017

• Detecting Large Reshare Cascades in Social Networks. K. Subbian, B. A. Prakash, and L. Adamic. In WWW, Perth, Australia. pp. 597-605, Apr 5-8, 2017. [PDF]

• Understanding Short-term Changes in Online Activity Sessions. F. Kooti, K.Subbian, W. A. Mason, L. Adamic, and K. Lerman, In WWW,  Perth, Australia. pp. 555-563, Apr 5-8, 2017. [PDF]

• Mining Social Streams: Models and Applications. K. Subbian and C. Aggarwal. In IEEE Data Eng. Bull. 40(3), pp. 100-109, 2017. [PDF]

2016

• Recommendations for Streaming Data. K. Subbian, C.Aggarwal, and K. Hegde. In CIKM,  Indianapolis, Indiana. pp. 2185-2190, Oct 24-28, 2016. [PDF]

• Querying and Tracking Influencers in Social Streams. K. Subbian, C.Aggarwal, and J. Srivastava. In WSDM,  San Francisco, California, pp. 493-502, Feb 22 - 25, 2016. [PDF]

• Mining Influencers Using Information Flows in Social Streams. K. Subbian, C.Aggarwal, and J. Srivastava. In Transactions of Knowledge Discovery and Data Mining (TKDD), 10(3), Jan 2016. [PDF]

2015

• Just in Time Recommendations: Modeling the Dynamics of Boredom in Activity Streams. K. Kapoor,  K. Subbian, J. Srivastava and P. Schrater. In WSDM, China, Feb 2 - 6, 2015. [PDF]

• PLUMS: Predicting Links Using Multiple Sources. K. Subbian, A. Banerjee and S. Basu. In SDM, Vancouver, Canada. Apr 30 - May 2, 2015. [PDF]

• Rare Class Detection in Networks. K. Subbian, C. Aggarwal, J. Srivastava and V. Kumar. In SDM, Vancouver, Canada. Apr 30 - May 2, 2015. [PDF] 

2014

• Scalable Information Flow Mining in Networks. K. Subbian, C. Sridhar, C. Aggarwal and J. Srivastava. In ECML, France, Sep 15 - 19, 2014. [PDF]

• Finding Influencers in Networks Using Social Capital. K. Subbian, D. Sharma, Z. Wen, and J. Srivastava. Journal of Social Network Analysis and Mining, 2014. [PDF]

• Evolutionary Network Analysis: A Survey, C. Aggarwal and K. Subbian, ACM Computing Surveys, 47(1), 2014. [PDF]

2013

• Content Centric Flow Mining for Influence Analysis in Social Streams. K. Subbian, C. Aggarwal, and J. Srivastava. In Conference on Information and Knowledge Management (CIKM), California, Oct 27 - Nov 1, 2013. [PDF]

• Dynamics of Trust Reciprocation in Heterogenous MMOG Networks. A. Singhal, K. Subbian, J. Srivastava, T. Kolda and A. Pinar. In Advances of Social Network and Mining (ASONAM), Canada, Aug 25 - Aug 28 2013. [PDF]

• Finding Influencers using Social Capital. K. Subbian, D. Sharma, Z. Wen, and J. Srivastava. In Advances of Social Network and Mining (ASONAM), Canada, Aug 25 - Aug 28 2013. [PDF]

• Community Detection With Prior Knowledge. K. Subbian, C. Aggarwal, J. Srivastava, and P. S. Yu. In the proceedings of Siam International Data Mining (SDM), Texas, May 2 - May 4, 2013. [PDF]

• Climate Multi-model Regression with Spatial Smoothing. K. Subbian and A. Banerjee. In the proceedings of Siam International Data Mining (SDM), Texas, May 2 - May 4, 2013. [PDF]

• Social Capital: The Power of Influencers in Networks. K. Subbian, D. Sharma, Z. Wen, and J. Srivastava. In Autonomous Agents and Multi Agent Systems (AAMAS), St. Paul, May 6- May 10, 2013. [PDF]

2012

• Learning to Rank for Robust Question Answering. A. Agarwal, H. Raghavan, K. Subbian, P. Melville, R. Lawrence, D. Gondek and J. Fan. In the proceedings of International Conference on Information and Knowledge Management (CIKM), Maui Hawaii, October 29 - November 2, 2012. [PDF]

• Event Detection in Social Streams. C. Aggarwal and K. Subbian. In the proceedings of Siam International Conference on Data Mining (SDM). Anaheim, California. April 26 - 28, 2012. [PDF]

• Dynamic Matrix Factorization: A State Space Approach. J. Sun, K. Varshney, and K. Subbian. In the proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Kyoto, Japan. March 25 - 30, 2012. [PDF]

2011

• Supervised Rank Aggregation for Predicting Influence in Networks. K. Subbian, and P. Melville. In the proceedings of the IEEE Conference on Social Computing (SocialCom), Boston. October 9 - 11, 2011. [PDF]

2010

• A Predictive Perspective on Measures of Influence in Networks: A Twitter Case Study 

• P. Melville, K. Subbian, C. Perlich, R. Lawrence, and E. Meliksetian. In the proceedings of the second Workshop on Information In Networks (WIN). New York. September 24 - 25, 2010.[PDF][PPT]

2009

• Nash Bargaining Based Ad Networks for Sponsored Search Auctions. R. Kannan, D. Garg, K. Subbian, Y. Narahari. IEEE Conference on Commerce and Enterprise Computing (CEC 2009), Vienna, Austria, July 20 - 23, 2009. [PDF]

2008

• A Nash Bargaining Approach to Retention Enhancing Bid Optimization in Sponsored Search Auctions With Discrete Bids. R. Kannan, D. Garg, K. Subbian, Y. Narahari. IEEE Conference on Automation Science and Engineering (CASE 2008), Washington DC, USA, August 23 - 26, 2008. [PDF]

• Design of Incentive Compatible Mechanisms for Ticket Allocation in Software Maintenance Services. Thesis submitted for Master of Science in Engineering, Indian Institute of Science, May 2008. [PDF]

2007

• Incentive Compatible Mechanisms for Group Ticket Allocation in Software Maintenance Services. K. Subbian, R. Kannan, R. K. Gautham, Y. Narahari. 14th Asia-Pacific Software Engineering Conference (APSEC 2007). 5-7 December 2007, Nagoya, Japan. [PDF]

• Truth Eliciting Mechanisms for Trouble Ticket Allocation in Software Maintenance Services. K.Subbian, Y.Narahari. Proceedings of the Nineteenth International Conference on Software Engineering & Knowledge Engineering (SEKE'2007), Boston, Massachusetts, USA, July 9 - 11, 2007. [PDF]

2006

• Migrate Visual Studio C and C++ projects to Eclipse CDT. P. Sampath, R. Kannan, K.Subbian. IBM Developerworks, 2006 [online]

• Enable C++ applications for Web service using XML-RPC. K. Subbian, R. Kannan. IBM Developerworks, 2006.[online]

2004

• Grid Services Programming and Application Enablement. L. Ferreira, A. Thakore, M. Brown, F.Lucchese, H. RuoBo, K. Subbian, L. Lin, P. Manesco, J. Mausolf, N. Momtaheni, O. Hernandez. IBM Publication, 2004. [PDF]