Prathamesh Mayekar

According to our database, Prathamesh Mayekar authored at least 16 papers between 2015 and 2024.

Collaborative distances:

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

2024

Wyner-Ziv Estimators for Distributed Mean Estimation With Side Information and Optimization.

Prathamesh Mayekar, Shubham K. Jha, Ananda Theertha Suresh, Himanshu Tyagi

IEEE Trans. Inf. Theory, April, 2024

2023

Compression for Distributed Optimization and Timely Updates.

Prathamesh Mayekar

CoRR, 2023

Fundamental Limits of Distributed Optimization over Multiple Access Channel.

Shubham K. Jha, Prathamesh Mayekar

Proceedings of the IEEE Information Theory Workshop, 2023

Communication-Constrained Bandits under Additive Gaussian Noise.

Prathamesh Mayekar, Jonathan Scarlett, Vincent Y. F. Tan

Proceedings of the International Conference on Machine Learning, 2023

2022

Fundamental Limits of Over-the-Air Optimization: Are Analog Schemes Optimal?

Shubham K. Jha, Prathamesh Mayekar, Himanshu Tyagi

IEEE J. Sel. Areas Inf. Theory, 2022

Wyner-Ziv compression is (almost) optimal for distributed optimization.

Prathamesh Mayekar, Shubham K. Jha, Himanshu Tyagi

Proceedings of the IEEE International Symposium on Information Theory, 2022

2021

RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization.

Prathamesh Mayekar, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2021

Information-constrained optimization: can adaptive processing of gradients help?

Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar, Himanshu Tyagi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information.

Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Optimal Source Codes for Timely Updates.

Prathamesh Mayekar, Parimal Parag, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2020

Limits on Gradient Compression for Stochastic Optimization.

Prathamesh Mayekar, Himanshu Tyagi

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

Finite Precision Stochastic Optimization - Accounting for the Bias.

Prathamesh Mayekar, Himanshu Tyagi

CoRR, 2019

2018

Optimal Lossless Source Codes for Timely Updates.

Prathamesh Mayekar, Parimal Parag, Himanshu Tyagi

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2016

Is Prevention Always Better? A Case of IT Service Management.

Prathamesh Mayekar, Veerendra Kumar Rai, Abhinay Puvvala, Harrick Mayank Vin

Proceedings of the 20th Pacific Asia Conference on Information Systems, 2016

Some algorithms for correlated bandits with non-stationary rewards: Regret bounds and applications.

Prathamesh Mayekar, Nandyala Hemachandra

Proceedings of the 3rd IKDD Conference on Data Science, 2016

2015

Performance analysis and decomposition results for some dynamic priority schemes in 2-class queues.

Prathamesh Mayekar, Jayendran Venkateswaran, Manu K. Gupta, Nandyala Hemachandra

Proceedings of the 13th International Symposium on Modeling and Optimization in Mobile, 2015