Sourangshu Bhattacharya

Preprints (Not peer-reviewed)

• In-Context Ability Transfer for Question Decomposition in Complex QA Venktesh V, Sourangshu Bhattacharya, Avishek Anand
  arXiv preprint arXiv:2310.18371 Link

Peer-reviewed Conferences and Journals

1. Sample Efficient Demonstration Selection for In-Context Learning
   Kiran Purohit, Venktesh V, Sourangshu Bhattacharya, Avishek Anand
   ICML 2025
   PDF-Link
   Github repository: link
    
2. CheckSelect: Online Checkpoint Selection for Flexible, Accurate, Robust, and Efficient Data Valuation
   Soumi Das , Manasvi Sagarkar , Suparna Bhattacharya , and Sourangshu Bhattacharya
   IEEE Transactions on Artificial Intelligence (TAI) (Accepted 2024)
   PDF-Link
   Github repository: link
    
3. EXPLORA: Efficient Exemplar Subset Selection for Complex Reasoning
   Kiran Purohit, Venktesh V., Raghuram Devalla, Krishna Mohan Yerragorla, Sourangshu Bhattacharya, Avishek Anand
   EMNLP 2024
   PDF-Link
    
4. A Greedy Hierarchical Approach to Whole-Network Filter- Pruning in CNNs.
   Kiran Purohit, Anurag Reddy Parvathgari, and Sourangshu Bhattacharya
   Transactions in Machine Learning Research. (accepted) 2024
   PDF-Link
    
5. A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning.
   Kiran Purohit, Soumi Das, Sourangshu Bhattacharya, and Santu Rana.
   European Conference on AI (ECAI) 2024
   PDF-Link
    
6. A Comparative Data-driven Study of Intensity-based Categorical Emotion Representations for MER
   Sanga Chaki, Sourangshu Bhattacharya, Junmoni Borgohain, Priyadarshi Patnaik, Raju Mullick, Gouri Karambelkar.
   IEEE Transactions on Affective Computing, (accepted) 2024.
   PDF-Link
    
7. VTruST: Controllable value function based subset selection for Data-Centric Trustworthy AI.
   Soumi Das, Shubhadip Nag, Shreyyash Sharma, Suparna Bhattacharya, Sourangshu Bhattacharya.
   ICLR DMLR workshop 2024 ARXIV-Link
    
8. Differentiable Change-point Detection With Temporal Point Processes
   Paramita Koley, Harshavardhan Alimi, Shrey Singla, Sourangshu Bhattacharya, Niloy Ganguly, Abir De.
   AISTATS 2023
   Link
    
9. 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
    
10. AR-BERT: Aspect-relation enhanced Aspect-level Sentiment Classification with Multi-modal Explanations.
    Sk Mainul Islam and Sourangshu Bhattacharya.
    TheWebConf 2022 Link
    Code Link
     
11. Offsetting Unequal Competition Through RL-Assisted Incentive Schemes
    Paramita Koley, Aurghya Maiti, Sourangshu Bhattacharya, Niloy Ganguly
    IEEE Transactions on Computational Social Systems 2022
12. 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
     
13. 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.
     
14. 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
     
15. Finding High-Value Training Data Subset through Differentiable Convex Programming.
    Soumi Das, Arshdeep Singh, Saptarshi Chatterjee, Suparna Bhattacharya, and Sourangshu Bhattacharya.
    ECML 2021. Link
     
16. 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.
     
17. 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)
     
18. Learning Temporal Point Processes with Intermittent Observations. Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De. International Conference on Artificial Intelligence and Statistics (AISTATS) 2021.
     
19. 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)
     
20. 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)
     
21. Scalable Backdoor Detection in Neural Networks. Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta and Svetha Venkatesh. ECML 2020.
    Link
     
22. 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)
     
23. 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
     
24. 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
     
25. 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
     
26. 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
     
27. 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
     
28. 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
     
29. 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
     
30. Shaping Opinion Dynamics in Social Networks Abir De, Sourangshu Bhattacharya, Niloy Ganguly International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018
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31. Demarcating Endogenous and Exogenous Opinion Diffusion Process on Social Networks Abir De, Sourangshu Bhattacharya, Niloy Ganguly The Web Conference 2018 (WWW 2018)
    Link
     
32. 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
     
33. 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
     
34. Forecasting Ad-Impressions on Online Retail Websites using Non-homogeneous Hawkes Processes Krunal Parmar, Samuel Bushi, Sourangshu Bhattacharya, and Surender Kumar CIKM 2017
    Link
     
35. 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
     
36. 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
     
37. 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
     
38. 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 .
     
39. 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
     
40. 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
     
41. 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
     
42. 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
     
43. 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
     
44. 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
     
45. 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
     
46. 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
     
47. Kernels on Attributed Pointsets with Applications. Mehul Parsana, Sourangshu Bhattacharya, Chiranjib Bhattacharya, K. R. Ramakrishnan. Neural Information Processing Systems (NIPS), 2007.
    PDF
     
48. Structural Alignment based Kernels for Protein Structure Classification. Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma R Chandra. International Conference on Machine Learning (ICML), 2007.
      Link
49. Comparison of protein structures by growing neighborhood alignments. Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma R Chandra. BMC Bioinformatics. 2007 Mar 6;8:77.
    Link
     
50. 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.