Sudeep Salgia

Orcid: 0000-0003-1361-4565

According to our database1, Sudeep Salgia authored at least 18 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Communication-Efficient Adaptive Algorithm for Federated Learning Under Cumulative Regret.
IEEE Trans. Signal Process., 2024

Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness.
CoRR, 2024

2023
Collaborative Learning in Kernel-Based Bandits for Distributed Users.
IEEE Trans. Signal Process., 2023

Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency.
CoRR, 2023

A Communication-Efficient Adaptive Algorithm for Federated Learning under Cumulative Regret.
CoRR, 2023

Provably and Practically Efficient Neural Contextual Bandits.
Proceedings of the International Conference on Machine Learning, 2023

Distributed Linear Bandits under Communication Constraints.
Proceedings of the International Conference on Machine Learning, 2023

2022
Disagreement-Based Active Learning in Online Settings.
IEEE Trans. Signal Process., 2022

Kernel-based Federated Learning with Personalization.
CoRR, 2022

Provably and Practically Efficient Neural Contextual Bandits.
CoRR, 2022

2021
As Easy as ABC: Adaptive Binning Coincidence Test for Uniformity Testing.
CoRR, 2021

A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Order-Optimal Adaptive Test Plan for Noisy Group Testing Under Unknown Noise Models.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
A Computationally Efficient Approach to Black-box Optimization using Gaussian Process Models.
CoRR, 2020

Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Stochastic Gradient Descent on a Tree: an Adaptive and Robust Approach to Stochastic Convex Optimization.
Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018
Bandlimited Spatiotemporal Field Sampling with Location and Time Unaware Mobile Sensors.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Spatial Field estimation from Samples taken at Unknown Locations generated by an Unknown Autoregressive Process.
CoRR, 2017


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