... somewhere something incredible is waiting to be known.

Latest Preprints

  • LearnDefend: Learning to Defend against Targeted Model-Poisoning Attacks on Federated Learning.
    Kiran Purohit, Soumi Das, Sourangshu Bhattacharya, and Santu Rana. at https://arxiv.org/abs/2305.02022
  • CheckSel: Efficient and Accurate Data-valuation Through Online Checkpoint Selection Soumi Das, Manasvi Sagarkar, Suparna Bhattacharya, Sourangshu Bhattacharya arXiv preprint arXiv:2203.06814 2022 Link

Peer-reviewed Conferences and Journals

  1. Differentiable Change-point Detection With Temporal Point Processes Paramita Koley, Harshavardhan Alimi, Shrey Singla, Sourangshu Bhattacharya, Niloy Ganguly, Abir De. Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6940-6955, 2023 Link
  2. Accurate and Efficient Channel pruning via Orthogonal Matching Pursuit. Kiran Purohit, Anurag Parvathgari, Soumi Das, and Sourangshu Bhattacharya. In Proceedings of the Second International Conference on AI-ML Systems, pp. 1-8. 2022. Link

  3. AR-BERT: Aspect-relation enhanced Aspect-level Sentiment Classification with Multi-modal Explanations. Sk Mainul Islam and Sourangshu Bhattacharya. TheWebConf 2022 Link Code Link
  4. Offsetting Unequal Competition Through RL-Assisted Incentive Schemes Paramita Koley, Aurghya Maiti, Sourangshu Bhattacharya, Niloy Ganguly IEEE Transactions on Computational Social Systems 2022
  5. MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related Microblogs. Rajdeep Mukherjee, Uppada Vishnu, Hari Chandana Peruri, Sourangshu Bhattacharya, Koustav Rudra, Pawan Goyal, Niloy Ganguly. WSDM 2022
  6. PASTE: A Tagging-free Decoding Framework using Pointer Networks for Aspect Sentiment Triplet Extraction. Rajdeep Mukherjee, Tapas Nayak, Yash Butala, Sourangshu Bhattacharya and Pawan Goyal. EMNLP 2021.
  7. TMCOSS: Thresholded Multi-Criteria Online Subset Selection for Data-Efficient Autonomous Driving. Soumi Das, Harikrishna Patibandla, Suparna Bhattacharya, Kshounis Bera, Niloy Ganguly, and Sourangshu Bhattacharya. ICCV 2021. Paper link
  8. Finding High-Value Training Data Subset through Differentiable Convex Programming. Soumi Das, Arshdeep Singh, Saptarshi Chatterjee, Suparna Bhattacharya, and Sourangshu Bhattacharya. ECML 2021. Link
  9. Learning Cross-Task Attribute - Attribute Similarity for Multi-task Attribute-Value Extraction. Mayank Jain, Sourangshu Bhattacharya, Harshit Jain, Karimulla Shaik and Muthusamy Chelliah. ECNLP workshop ACL 2021.
  10. Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach. Paramita Koley, Avirup Saha, Sourangshu Bhattacharya, Niloy Ganguly and Abir De. ACM Transactions on Knowledge Discovery from Data TKDD. (accepted)
  11. Learning Temporal Point Processes with Intermittent Observations. Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De. International Conference on Artificial Intelligence and Statistics (AISTATS) 2021.
  12. An Optimized Distributed Recursive Matrix Multiplication for Arbitrary Sized Matrices. Utkarsh Parasrampuria, Chandan Misra, and Sourangshu Bhattacharya.  IEEE International Conference on Big Data, 2020. (poster)
  13. On Distributed Solution for Simultaneous Linear Symmetric Systems. Chandan Misra, Utkarsh Parasarampuria, Sourangshu Bhattacharya, and Soumya K. Ghosh. IEEE International Conference on Big Data, 2020. (poster)
  14. Scalable Backdoor Detection in Neural Networks. Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta and Svetha Venkatesh. ECML 2020.
    Link
  15. Explaining Perceived Emotion Predictions in Music: An Attentive Approach Sanga Chaki, Pranjal Doshi, Sourangshu Bhattacharya, Priyadarshi Patnaik. International Symposium on Music Information Retrieval, 2020. (paper)
  16. A fast and scalable distributed kriging algorithm using Spark framework. Chandan Misra, Sourangshu Bhattacharya, and Soumya K. Ghosh. International Journal of Data Science and Analytics (2020), Springer.
    Link
  17. Read what you need: Controllable Aspect-based Opinion Summarization of Tourist Reviews Rajdeep Mukherjee, Hari Chandana Peruri, Uppada Vishnu, Pawan Goyal, Sourangshu Bhattacharya and Niloy Ganguly. ACM SIGIR 2020 (Short paper)
    Link
  18. Multi-criteria online Frame-subset Selection for Autonomous Vehicle Videos Soumi Das, Sayan Mandal, Ashwin Bhoyar, Madhumita Bharde, Niloy Ganguly, Suparna Bhattacharya, and Sourangshu Bhattacharya. Pattern Recognition Letters (2020)
    Link
  19. Stark: Fast and Scalable Strassen's Matrix Multiplication using Apache Spark Chandan Misra, Sourangshu Bhattacharya, and Soumya K. Ghosh. IEEE Transactions on Big Data (2020)
    Link
  20. Learning Linear Influence Models in Social Networks from Transient Opinion Dynamics Abir De, Sourangshu Bhattacharya, Parantapa Bhattacharya, Niloy Ganguly, and Soumen Chakrabarti. ACM Transactions on the Web (TWEB) 13, no. 3 (2019): 1-33.
    Link
  21. Probabilistic Path Planning using Obstacle Trajectory Prediction Vasudha Todi, Gunjan Sengupta and Sourangshu Bhattacharya ACM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD) 2019
    Link
  22. Non-link Preserving Network Embedding using Subspace Learning for Network Reconstruction Pradumn Kumar Pandey, Sourangshu Bhattacharya and Niloy Ganguly ACM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD) 2019
    Link
  23. Shaping Opinion Dynamics in Social Networks Abir De, Sourangshu Bhattacharya, Niloy Ganguly International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018
    Link
  24. Demarcating Endogenous and Exogenous Opinion Diffusion Process on Social Networks Abir De, Sourangshu Bhattacharya, Niloy Ganguly The Web Conference 2018 (WWW 2018)
    Link
  25. Task-Specific Representation Learning for Web-scale Entity Disambiguation. Rijula Kar, Susmija Reddy, Sourangshu Bhattacharya, Anirban Dasgupta, Soumen Chakrabarti AAAI Conference on Artificial Intelligence (AAAI-18) pdf
    Link
  26. SPIN: A Fast and Scalable Matrix Inversion Method in Apache Spark. Chandan Misra, Swastik Haldar, Sourangshu Bhattacharya, Soumya K. Ghosh. International Conference on Distributed Computing and Networking (ICDCN) 2018
    Link
  27. Forecasting Ad-Impressions on Online Retail Websites using Non-homogeneous Hawkes Processes Krunal Parmar, Samuel Bushi, Sourangshu Bhattacharya, and Surender Kumar CIKM 2017
    Link
  28. SLANT+: A Nonlinear Model for Opinion Dynamics in Social Networks Bhushan Kulkarni, Sumit Agarwal, Abir De, Sourangshu Bhattacharya, and Niloy Ganguly ICDM 2017 (Short paper)
    Link
  29. Link Travel Time Prediction and Route Recommendation from Large Scale Endpoint Data, Sankarshan Mridha, Niloy Ganguly and Sourangshu Bhattacharya. ACM SIGSPATIAL 2017 . (Short paper)
    Link
  30. Mining Twitter and Taxi Data for Predicting Taxi Pickup Hotspots Sankarshan Mridha, Sayan Ghosh, Robin Singh, Sourangshu Bhattacharya and Niloy Ganguly ASONAM 2017 . (Short paper)
    Link
  31. Cloud Computing-Based Non-Invasive Glucose Monitoring for Diabetic Care PP Pai, PK Sanki, SK Sahoo, A De, S Bhattacharya, S Banerjee
    IEEE Transactions on Circuits and Systems I: Regular papers, 2017 .
  32. Distributed Weighted Parameter Averaging for SVM Training on Big Data Ayan Das, Raghuveer Chanda, Smriti Agrawal and Sourangshu Bhattacharya AAAI 2017 Workshop on Distributed Machine Learning . pdf
    Link
  33. Learning and Forecasting Opinion Dynamics in Social Networks. Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya and Manuel Gomez Rodriguez Annual Conference on Neural Information Processing Systems (NIPS) 2016.
    Link
  34. Discriminative Link Prediction using Local, Community, and Global Signals. Abir De, Sourangshu Bhattacharya, Sourav Sarkar, Niloy Ganguly, and Soumen Chakrabarti IEEE Transactions On Knowledge And Data Engineering (TKDE), Vol. 28, No. 8, August 2016.
    Link
  35. Regularized least squares regression for calibration of a photoacoustic spectroscopy based non-invasive glucose monitoring system Praful P Pai, Sourangshu Bhattacharya, Swapna Banerjee IEEE International Ultrasonics Symposium (IUS), 2015
    Link
  36. Learning a Linear Influence Model from Transient Opinion Dynamics. Abir De, Sourangshu Bhattacharya, Parantapa Bhattacharya, Niloy Ganguly, Soumen Chakrabarti. ACM International Conference on Information and Knowledge Management (CIKM), 2014.
    Link
  37. Segmenting Web-Domains and Hashtags using Length Specific Models. Sriram Srinivasan, Sourangshu Bhattacharya, Rudrasis Chakraborty. ACM International Conference on Information and Knowledge Management (CIKM), 2012.
    Link
  38. Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators. Dinesh Garg, Sourangshu Bhattacharya, Sundararajan Sellamanickam, Shirish Shevade. Conference on Uncertainty in Artificial Intelligence (UAI), 2012.
    PDF
  39. Robust Formulations for Handling Uncertainty in Kernel Matrices. Sahely Bhadra, Sourangshu Bhattacharya, Chiranjib Bhattacharyya, Aharon Ben-Tal. International Conference on Machine Learning (ICML), 2010.
    PDF
  40. Kernels on Attributed Pointsets with Applications. Mehul Parsana, Sourangshu Bhattacharya, Chiranjib Bhattacharya, K. R. Ramakrishnan. Neural Information Processing Systems (NIPS), 2007.
    PDF
  41. Structural Alignment based Kernels for Protein Structure Classification. Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma R Chandra. International Conference on Machine Learning (ICML), 2007.
    Link
  42. Comparison of protein structures by growing neighborhood alignments. Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma R Chandra. BMC Bioinformatics. 2007 Mar 6;8:77.
    Link
  43. Projections for fast protein structure retrieval. Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma R. Chandra. BMC Bioinformatics. 2006 Dec 18;7 Suppl 5:S5.
    Link

Book Chapters

  • Kernels on Protein Structures. Sourangshu Bhattacharya, Chiranjib Bhattacharyya, and Nagasuma R. Chandra. In Computational Intelligence and Pattern Analysis in Biology Informatics, John Wiley & Sons, Inc., New York, USA. Link

Peer-reviewed Posters and Workshop Papers

  1. Learning to tokenize web domains. Sriram Srinivasan, Sourangshu Bhattacharya. International Conference on World Wide Web, WWW 2011 (poster).
  2. Budgeted PAC Learning with Two Noisy Annotators. Dinesh Garg, Sundararajan Sellamanickam, Sourangshu Bhattacharya, Shirish Shevade. Budgeted Learning Workshop, ICML 2010.