Research 

Journal Publications:

1. ** Sparsifying Count Sketch. Bhisham Dev Verma, Rameshwar Pratap, Punit Pankaj Dubey. Accepted to the Information Process Letter, 2024. 

2. **Unbiased Estimation of Inner Product via Higher Order Count Sketch. Bhisham Dev Verma, Rameshwar Pratap, and Manoj Thakur. In the Information Process Letters, Volume 183, 106407, 2024. (Paper Link)

3. *One-pass additive-error subset selection for $\ell_{p}$ subspace approximation and $(k,p)$-clustering. Amit Deshpande and Rameshwar Pratap. In the Algorithmica, volume 85, number 10, pages 3144--3167, 2023. (Paper Link.)

4. * QUINT: Node embedding using network hashing. Debajyoti Bera, Rameshwar Pratap, Bhisham Dev Verma, Biswadeep Sen, and Tanmoy Chakraborty. In the IEEE Transactions on Knowledge and Data Engineering (IEEE-TKDE), 35(3): 2987-3000 (2023). (Paper link). 

5. Dimensionality Reduction for Categorical Data. Debajyoti Bera, Rameshwar Pratap, and Bhisham Dev Verma. In the IEEE Transactions on Knowledge and Data Engineering (IEEE-TKDE), 35(4): 3658-3671 (2023). (Paper link.)

6. *On the Complexity of Algebraic Numbers, and the Bit-Complexity of Straight-Line Programs. Eric Allender, Nikhil Balaji, Samir Datta,   Rameshwar Pratap. In the Computability (The Journal of the Association of Computability in Europe), 12(2): 145-173 (2023). (Paper Link.) 

7. ** Variance reduction in Feature Hashing using MLE and Control Variate Method. Bhisham Dev Verma, Rameshwar Pratap, and Manoj Thakur. In the Machine Learning, 111(7): 2631-2662. (Paper Link.) https://doi.org/10.1007/s10994-022-06166-z 

8. ** Efficient Binary Embedding of Categorical Data using BinSketch. Bhisham Dev Verma, Rameshwar Pratap, and Debajyoti Bera. In the Data Mining and Knowledge Discovery, 36(2): 537-565, 2022. (Paper link).

9. * Sampling-based dimension reduction for subspace approximation with outliers. Amit Deshpande, and  Rameshwar Pratap.  In the Theoretical Computer Science, 858: 100-113 (2021). (Paper link) 

10. * Helly-Type Theorems in Property Testing.  Sourav Chakraborty, Rameshwar Pratap, Sasanka Roy, and Shubhangi Saraf.  In the International Journal of Computational Geometry and Applications (IJCGA).  Volume 28, Issue 04, pages 365–379, December 2018. https://doi.org/10.1142/S0218195918500115.

11. * Testing whether the Uniform Distribution is a Stationary Distribution.  Sourav Chakraborty, Akshay Kamath, and Rameshwar Pratap. In Information Processing Letters, volume 116(7), pages 475-480, 2016. (Paper link) (slides). 

Conference Publications:

1. ** Towards obtaining SEP via Orthogonality of Projection Matrix in massive MIMO Networks. Gopal   Chamarthi, Adarsh Patel, Rameshwar Pratap. Accepted to the IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS'23)-Early Research Forum, 2023.  

2. *Minwise-Independent Permutations with Insertion and Deletion of Features.  Rameshwar Pratap and Raghav Kulkarni.  In the 16th International Conference on Similarity Search and Applications, SISAP, volume  14289, pages 171--184,  2023. (preprint link.)

3. **Random Projection Based Efficient Detectors In Massive MIMO Communication Networks. Gopal  Chamarthi, Adarsh Patel, Rameshwar Pratap.  Accepted to the IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2023. (Paper link).

4. **Improving Sign-Random-Projection via Count Sketch. Punit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, and Keegan Kang.  In the 38th Conference on Uncertainty in Artificial Intelligence (UAI), pages 599-609, 2022. (Paper link.) (poster.)

5. *One-pass additive-error subset selection for \ell_p subspace approximation. Amit Deshpande

 Rameshwar Pratap. In the 49th EATCS International Colloquium on Automata, Languages  and Programming (ICALP), pages 51:1-51:14,  2022. (Paper link.) (slides.)

6. * Variance Reduction in Frequency Estimators via Control Variates Method. Rameshwar Pratap and Raghav Kulkarni. In the Association for Uncertainty in Artificial Intelligence - UAI 2021, pages 183-193. (Paper link.) (slides).

7.  Improving Hashing Algorithms for Similarity Search via MLE and the Control Variates Trick. Keegan Kang, Sergey Kushnarev, Weipin Wong, Rameshwar Pratap, Haikal Yeo, Yijia Chen.  In  the 13th Asian Conference on Machine Learning (ACML 2021), pages 814-829. (Paper link)

8. * Feature Hashing with Insertion and Deletion of Features. Rameshwar Pratap, Hrushikesh Sudam Sarode, Suryakant Bhardwaj and Raghav Kulkarni. In the IEEE-Bigdata, pages 888-898, 2021. (Paper link).

9. * Improving Tug-of-War sketch using Control-Variates method. Rameshwar Pratap, Bhisham Dev Verma and Raghav Kulkarni. In the SIAM Conference on Applied and Computational Discrete Algorithms, (ACDA21), pages 66-76, 2021. (Paper link.) (slides (slides courtesy Bhisham.))

10. * Randomness Efficient Feature Hashing for Sparse Binary Data.   Rameshwar Pratap, Karthik Revanuru, Anirudh Ravi, Raghav Kulkarni. In  the 12th Asian Conference on Machine Learning (ACML 2020), pages 689-704, 2020. (Paper link).

11. * Scaling up Simhash. Rameshwar Pratap, Anup Deshmukh, Pratheeksha Nair, Anirudh Ravi. In the 12th Asian Conference on Machine Learning (ACML 2020), pages 705-720, 2020.  (Paper link). Invited for Special Issue in Springer Nature Computer Science.

12. * Subspace approximation with outliers. Amit Deshpande  and Rameshwar Pratap. In the 26th International Computing and Combinatorics Conference - COCOON,  pages 1-13,  2020. Winner of the Best Paper Award at COCOON 2020. (Paper link.)

13. * Robust k-means++. Amit Deshpande, Praneeth Kacham and Rameshwar Pratap. In the Association for Uncertainty in Artificial Intelligence - UAI 2020, pages 799-808. (Paper link.) (Code.)

14.  IHashNet: Iris Hashing Network based on efficient multi-index hashing. Avantika Singh, Pratyush Gaurav, Chirag Vashist, Aditya Nigam and Rameshwar Pratap. In the International Joint Conference On Biometrics IJCB 2020, pages 1-9, 2020.

15. * Efficient Compression Algorithm for Multimedia Data. Rameshwar Pratap, Karthik Revanuru, Anirudh Ravi and Raghav Kulkarni. In the IEEE International Conference on Multimedia Big Data (IEEE-BigMM), pages 245-250,  2020.  

16. * Efficient Sketching Algorithm for Sparse Binary Data.  Rameshwar Pratap, Debajyoti Bera, and Karthik Revanuru. In IEEE- ICDM (International Conferences of Data Mining),  pages 508-517, 2019.  (Paper link.)  (Code.)

17. * Efficient Dimensionality Reduction for Sparse Binary Data. Rameshwar Pratap, Raghav Kulkarni, and Ishan Sohony.  In the IEEE International Conference on Big Data (Big Data), pages 152-157, 2018. (Paper link).

18. * A Faster Sampling Algorithm for Spherical k-means. Rameshwar Pratap, Anup Deshmukh, Pratheeksha Nair, and Tarun Dutt.  In The 10th Asian Conference on Machine Learning, ACML, pages 343-358, 2018. (Paper link) (Code).

19. * Efficient Compression Technique for Sparse Sets.  Rameshwar Pratap, Ishan Sohony and Raghav Kulkarni. In the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pages 164-176, 2018. (Paper link). (Slides)

20. * Faster Coreset Construction for Projective Clustering via Low-Rank Approximation. Rameshwar Pratap and Sandeep Sen. In the International Workshop on Combinatorial Algorithms (IWOCA), pages 336-348, 2018. (Paper link) (Slides). 

21. ** Ensemble Learning for Credit Card Fraud Detection.  Ishan Sohony, Rameshwar Pratap and Ullas Nambiar.  In CoDS-COMAD (Industry track), pages 289-294, 2018. 

22. * Frequent-Itemset Mining using Locality-Sensitive Hashing. Debajyoti Bera and Rameshwar Pratap. In the International Computing and Combinatorics Conference (COCOON), pages 143-155, 2016. (Paper link).(slides)

23. * Helly-Type Theorems in Property Testing.  Sourav Chakraborty, Rameshwar Pratap, Sasanka Roy and Shubhangi Saraf. In the Latin American Theoretical INformatics Symposium (LATIN), pages 306-317, 2014. (Paper link) (slides).

24. * Testing Uniformity of Stationary Distribution.  Sourav Chakraborty, Rameshwar Pratap and Akshay Kamath. In the European Conference on Combinatorics, Graph Theory and Applications (EuroComb), pages 589-594, 2013.  

Also accepted to the Cologne-Twente Workshop on Graphs & Combinatorial Optimization (CTW), pages 47-50, 2013. 

25. * Computing Bits of Algebraic Numbers.  Samir Datta and Rameshwar Pratap. In the Theory and  Applications of Models of Computation (TAMC), pages 189-201, 2012. (Paper link) (slides)

Un-refereed Papers/ preprint

1. *Improved Outlier Robust Seeding for k-means. Amit Deshpande and Rameshwar Pratap. (Paper link).

Patents:

1. Method, device, and system for clustering document objects based on information content. Manjunath Ramachandra Iyer, Boby Chaitanya Villari, Rameshwar Pratap. Patent office US. Patent number 11232132. Application number 16260212. Publication date 2022/1/25. 

2.  Method and a system for context based clustering of object. Manjunath Ramachandra Iyer, Rameshwar Pratap, Boby Chaitanya Villari. Patent office US. Patent number 11537938. Application number 16370900. Publication date 2022/12/27. 

* Papers in which I am the primary author (Data Science/ Machine Learning forum) or an equal author (Theoretical Computer Science forum).

**Papers whose lead authors are either my students or have been closely  mentored by me.

Research Collaborators:

Eric Allender                Distinguished Professor at Rutgers University, USA

Nikhil Balaji Faculty at IIT Delhi

Debajyoti Bera              Faculty at IIIT Delhi

Sourav Chakraborty     Faculty at ISI Kolkata

Samir Datta                   Faculty at Chennai Mathematical Institute, CMI

Anup Deshmukh          PhD student at the University of Waterloo

Amit Deshpande          Researcher at Microsoft Research, India

   Bhisham Dev Verma     PhD student at IIT Mandi

   Tarun Dutt                     Research Assistant at Sigtuple

   Gopal Chamarthi          PhD student at IIT Mandi 

    Keegan Kang                 Faculty at SUTD Singapore

    Adarsh Patel                 Faculty at IIT Mandi

    Manoj Thakur              Faculty at IIT Mandi

         Sergey Kushnarev        Faculty at John Hopkins University

Pratyush Gaurav          UG student at IIT Mandi

Praneeth Kacham        PhD student at CMU

Akshay Kamath           PhD student at University of Texas at Austin

Raghav Kulkarni          Adjunct faculty at Chennai Mathematical Institute, CMI

Pratheeksha Nair         PhD Student at ‎McGill University, Canada

Ullas Nambiar              Principal Director AI, Accenture

Aditya Nigam               Faculty at IIT Mandi

Anirudh Ravi                Data Science at Amgen

Karthik Revanuru        Data Scientist at CRED

Sasanka Roy                 Faculty at ISI Kolkata 

Shubhangi Saraf          Faculty at Rutgers University

Sandeep Sen                 Faculty at IIT Delhi

Avantika Singh             PhD student at IIT Mandi

Ishan Sohony                Software Engineer at Amazon (AWS) Seattle

Chirag Vashist             UG student at IIT Mandi 

Wei Pin Wong              Faculty at SUTD Singapore

  Names are arranged in alphabetical order.