Anirban Dasgupta
Professor, Computer Science and Engineering, IIT Gandhinagar
Current citation data available at Google Scholar profile.
Pre-publication prints for refereed conferences and journal papers
Saving Critical Nodes with Firefighters is FPT
Jayesh Choudhari, Anirban Dasgupta, Neeldhara Misra and Ramanujan M. S.. ICALP 2017
Caching with dual costs.
Anirban Dasgupta, Ravi Kumar and Tamas Sarlos. WWW 2017.
A Framework for Estimating Stream Expression Cardinalities.
Anirban Dasgupta, Kevin Lang, Lee Rhodes and Justin Thaler, to appear in International Conference of Database Technologies (ICDT) 2016. Best newcomer award.
On Sampling Nodes in a Network
Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi and Tamas Sarlos., to appear in Conference of the World Wide Wed (WWW) 2016.
Flavio Chierichetti, Abhimanyu Das, Anirban Dasgupta, Ravi Kumar
in Proceedings of FOCS 2015
On Learning Mixture Models for Permutations
Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi
in Proceedings of ITCS 2015
On Reconstructing a Hidden Permutation
Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi
to appear in Proceedings of RANDOM 2014
On Estimating Average degree of Networks
Anirban Dasgupta, Ravi Kumar, Tamas Sarlos, WWW 2014.
Learning Entangled Single Sample Gaussians
Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi, SODA 2014.
Summarization through Submodularity and Dispersion
Anirban Dasgupta, Ravi Kumar, Sujith Ravi, Proceeding of 51st Annual Meeting of the Association for Computational Linguistics (ACL) 2013.
Crowdsourced Judgement Elicitation with Endogenous Proficiency
Anirban Dasgupta, Arpita Ghosh, Proceeding of 22nd ACM International World Wide Web Conference (WWW) 2013.
Aggregating Crowdsourced Binary Ratings
Nilesh Dalvi, Anirban Dasgupta, Ravi Kumar and Vibhor Rastogi, Proceedings of 22nd ACM International World Wide Web Conference (WWW) 2013.
Optimal Hashing Schemes for Entity Matching
Nilesh Dalvi, Vibhor Rastogi, Anirban Dasgupta, Anish Das Sarma and Tamas Sarlos, Proceedings of 22nd ACM International World Wide Web Conference (WWW) 2013.
Selecting Diverse Features via Spectral Regularization.
Abhimanyu Das, Anirban Dasgupta, Ravi Kumar. NIPS 2012.
Impact of Spam Exposure on User Engagement.
Anirban Dasgupta, Kunal Punera, Justin Rao, Xuanhui Wang, USENIX Security 2012.
Sparse and Lopsided Set Disjointness via Information Theory.
Anirban Dasgupta, Ravi Kumar, D. Sivakumar, RANDOM-APPROX 2012.
Anirban Dasgupta, Ravi Kumar, D. Sivakumar, KDD 2012.
Vote Calibration in Community Question-Answering Systems.
Bee-Chung Chen, Anirban Dasgupta, Xuanhui Wang, Jie Yang, SIGIR 2012.
Estimating Unique browsers through clustering browser cookies.
Anirban Dasgupta, Maxim Gurevich, Liang Zhang, Belle Tseng, Achint Thomas, ACM Conference on Web-search and Data Mining (WSDM), 2012.
Fast Locality Sensitive Hashing.
Anirban Dasgupta, Ravi Kumar, Tamas Sarlos, ACM-SIGKDD Conference on Knowledge Discovery and Data Mining 2011.
Spam or ham? characterizing and detecting fraudulent “not spam” reports in web mail systems.
Anirudh Ramachandran, Anirban Dasgupta, Nick Feamster, Kilian Weinberger, Conference on Email and Anti-spam, 2011.
On Scheduling in Map-reduce and Flowshops.
Ben Moseley, Anirban Dasgupta, Ravi Kumar, Tamas Sarlos, ACM Symposium on Parallelism in Algorithms and Architecture(SPAA) 2011.
Enhanced Email Spam Filtering through combining Similarity Graphs.
Anirban Dasgupta, Maxim Gurevich, Kunal Punera, ACM Conference on Web-search and Data Mining(WSDM) 2011.
A Sparse Johnson-Lindenstrass Transform.
Anirban Dasgupta, Ravi Kumar and Tamas Sarlos, ACM Symposium on Theory of Computing, June 2010.
Collaborative Spam Filtering with the Hashing Trick.
Josh Attenberg, Kilian Weinberger, Alex Smola, A. Dasgupta, Martin Zinkevich, Sixth Conference on Email and Anti-Spam, 2009. Appeared in the online Virus Bulletin November 2009 issue by invitation: http://www.virusbtn.com/virusbulletin/archive/2009/11/vb200911-collaborative-spam-filtering.
Feature hashing for large scale multitask learning.
Kilian Weinberger, Anirban Dasgupta, John Langford, Alex Smola and Josh Attenberg, International Conference of Machine Learning, 2009.
Online story scheduling in web advertising.
Arpita Ghosh, Anirban Dasgupta, Hamid Nazerzadeh and Prabhakar Raghavan, Proceedings of 20th Annual ACM-SIAM Symposium on Discrete Algorithms 2009, pages 1275-1284.
Sampling algorithms and coresets for $\ell_p$ regression.
Anirban Dasgupta, Petros Drineas, Boulos Harb, Ravi Kumar, and Michael
Mahoney, Conference version in SIAM Symposium on Discrete Algorithms, 2008.
Journal version in SIAM Journal of Computing volume 38(5), 2009, pages 2060-2078.
De-duping URLs via Rewrite Rules.
Anirban Dasgupta, Amit Sasturkar and Ravi Kumar, Proceedings of 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2008, pages 186-194.
Approximation Algorithms for Co-clustering.
Aris Anagnostopoulos, Anirban Dasgupta and Ravi Kumar,
Proceedings of ACM Conference on Principles of Database Systems 2008, pages 201-210.
Statistical Properties of Community Structure in Large Social and Information Networks. (arXiv, conference)
Jure Leskovec, Kevin Lang, Anirban Dasgupta and Michael Mahoney,
Proceedings of 17th International Conference on World Wide Web 2008, page 695-704.
Journal version appeared in Internet Mathematics, 6(1), 29-123 (2009).
Feature Selection Methods for Text Classification.
Anirban Dasgupta, Petros Drineas, Boulos Harb, Vanja Josifovski, and Michael
Mahoney, Proceedings of 13th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2007, pages 230-239.
The Discoverability of the Web.
Anirban Dasgupta, Arpita Ghosh, Ravi Kumar, Chris Olston, Sandeep Pandey, and Andrew Tomkins, Proceedings of 16th International Conference on World Wide Web 2007, pages 421-430.
Spectral Clustering with Limited Independence.
Anirban Dasgupta, John Hopcroft, Ravi Kannan, and Pradipta Mitra,
Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete algorithms, 2007, pages 1036 – 1045.
Finding (short) paths in social networks.
Andre Allavena, Anirban Dasgupta, John Hopcroft, and Ravi Kumar,
Internet Mathematics volume 3 issue 2, 2006, pages 129-146.
Spectral Clustering by Recursive Partitioning.
Anirban Dasgupta, John Hopcroft, Ravi Kannan, and Pradipta Mitra,
Proceedings of 14th Annual European Symposium on Algorithms 2006, pages 256-267.
On learning mixtures of heavy tailed distributions.
Anirban Dasgupta John Hopcroft, Jon Kleinberg, and Mark Sandler,
Proceedings of 46th Annual IEEE Symposium on Foundations of Computer Science 2005, pages 491-500.
Variable Latent Semantic Indexing.
Anirban Dasgupta, Prabhakar Raghavan, Ravi Kumar, and Andrew Tomkins,
Proceedings of 11th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2005, pages 13-21.
Spectral Analysis of Random Graphs with Skewed Degree Distributions.
Anirban Dasgupta, John Hopcroft, and Frank McSherry,
Proceedings of 45th Annual IEEE Symposium on Foundations of Computer Science 2004, pages 602-610.
The price of stability for network design with fair cost allocation. (conference, journal)
Elliot Anshelevich, Anirban Dasgupta, Jon Kleinberg,
Eva Tardos, Tom Wexler, and Tim Roughgarden, Foundations of Computer Science 2004.
Journal version appeared in SIAM Journal on Computing, Volume 38, Issue 4 (November 2008), pages 1602-1623.
Near Optimal Network Design with Selfish Agents.
Elliot Anshelevich, Anirban Dasgupta, Eva Tardos, and Tom Wexler, Symposium on Theory of Computing 2003.
Journal version appeared in Theory of Computing, Volume 4 (2008), pages 77-109.
Quantified Computation Tree Logic.
Anindya Patthak, Indrajit Bhattacharya, Anirban Dasgupta, Pallab Dasgupta, and Partha Pratim Chakrabarti, Information Processing Letters Vol 82(3), 2002.
Patents
Mail compression scheme with individual message decompressability, with Ravi Kumar. US Patent number US78360
Feature selection for text classification using subspace sampling, with Petros Drineas, Boulos Harb, Vanja Josifovski, Michael Mahoney. US Patent number US8046317.
Some of the course material can be accessed only by using an IITGN account.
- Archived videos of NPTEL course on ‘Scalable Data Science’, co-taught with Sourangshu Bhattacharya.
- Introduction to Data Science (CS 328)
- Algorithms (CS610)
- Fall 2017, Fall 2019
- Special topics in ML (CS 691)
- I had the opportunity to give a talk on Alan Turing in a virtual seminar series at IITGN. The talk draws heavily from the beautiful Logicomix book by Apostolos Doxiadis and Christos Papadimitriou. Here is an article written by the talented Apeksha Srivastava based on the talk.