Sutanu Gayen

According to our database, Sutanu Gayen authored at least 15 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu.

Arnab Bhattacharyya, Sutanu Gayen, Eric Price, Vincent Y. F. Tan, N. V. Vinodchandran

SIAM J. Comput., June, 2023

Total Variation Distance Estimation Is as Easy as Probabilistic Inference.

Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

Electron. Colloquium Comput. Complex., 2023

On Approximating Total Variation Distance.

Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Efficient interventional distribution learning in the PAC framework.

Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Vedant Raval, N. Variyam Vinodchandran

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning Sparse Fixed-Structure Gaussian Bayesian Networks.

Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Efficient inference of interventional distributions.

Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Vedant Raval, N. V. Vinodchandran

CoRR, 2021

Near-optimal learning of tree-structured distributions by Chow-Liu.

Arnab Bhattacharyya, Sutanu Gayen, Eric Price, N. V. Vinodchandran

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Testing Product Distributions: A Closer Look.

Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran

Proceedings of the Algorithmic Learning Theory, 2021

2020

Perfect Zero Knowledge: New Upperbounds and Relativized Separations.

Peter Dixon, Sutanu Gayen, A. Pavan, N. V. Vinodchandran

IACR Cryptol. ePrint Arch., 2020

Efficiently Learning and Sampling Interventional Distributions from Observations.

Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, N. V. Vinodchandran

CoRR, 2020

Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning.

Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, N. V. Vinodchandran

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning and Sampling of Atomic Interventions from Observations.

Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, N. Variyam Vinodchandran

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

New Algorithms for Distributed Sliding Windows.

Sutanu Gayen, N. V. Vinodchandran

Proceedings of the 16th Scandinavian Symposium and Workshops on Algorithm Theory, 2018

KmerEstimate: A Streaming Algorithm for Estimating k-mer Counts with Optimal Space Usage.

Sairam Behera, Sutanu Gayen, Jitender S. Deogun, N. V. Vinodchandran

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

2016

Algorithms for k-median Clustering over Distributed Streams.

Sutanu Gayen, N. V. Vinodchandran

Proceedings of the Computing and Combinatorics - 22nd International Conference, 2016