Kushal Chakrabarti

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 25

Top Topics

Linear Regression

Theoretic Framework

Machine Learning

Top Venues

IEEE Control. Syst. Lett.

Publications

Kushal Chakrabarti, Mayank Baranwal
A Methodology Establishing Linear Convergence of Adaptive Gradient Methods under PL Inequality. CoRR (2024)
Kushal Chakrabarti, Nikhil Chopra
On Convergence of the Iteratively Preconditioned Gradient-Descent (IPG) Observer. IEEE Control. Syst. Lett. 8 (2024)
Kushal Chakrabarti, Nikhil Chopra
A control theoretic framework for adaptive gradient optimizers. Autom. 160 (2024)
Kushal Chakrabarti, Nikhil Chopra
On Convergence of the Iteratively Preconditioned Gradient-Descent (IPG) Observer. CoRR (2024)
Dhruv Srinivasan, Kushal Chakrabarti, Nikhil Chopra, Avik Dutt
Quantum Circuit Optimization through Iteratively Pre-Conditioned Gradient Descent. QCE (2023)
Kushal Chakrabarti, Mayank Baranwal
Linear Convergence of Pre-Conditioned PI Consensus Algorithm under Restricted Strong Convexity. CoRR (2023)
Tianchen Liu, Kushal Chakrabarti, Nikhil Chopra
Iteratively Preconditioned Gradient-Descent Approach for Moving Horizon Estimation Problems. CDC (2023)
Tianchen Liu, Kushal Chakrabarti, Nikhil Chopra
Iteratively Preconditioned Gradient-Descent Approach for Moving Horizon Estimation Problems. CoRR (2023)
Kushal Chakrabarti, Nikhil Chopra
IPG Observer: A Newton-Type Observer Robust to Measurement Noise. ACC (2023)
Kushal Chakrabarti, Nikhil Chopra
Analysis and Synthesis of Adaptive Gradient Algorithms in Machine Learning: The Case of AdaBound and MAdamSSM. CDC (2022)
Kushal Chakrabarti, Nikhil Chopra
A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning. CoRR (2022)
Kushal Chakrabarti, Amrit S. Bedi, Fikadu T. Dagefu, Jeffrey N. Twigg, Nikhil Chopra
Fast Distributed Beamforming without Receiver Feedback. IEEECONF (2022)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem. Autom. 137 (2022)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations. IEEE Trans. Control. Netw. Syst. 9 (2) (2022)
Kushal Chakrabarti, Nikhil Chopra
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective. CDC (2021)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. IEEE Control. Syst. Lett. 5 (6) (2021)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. ACC (2021)
Kushal Chakrabarti, Nikhil Chopra
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective. CoRR (2021)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. CoRR (2021)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
On Accelerating Distributed Convex Optimizations. CoRR (2021)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning. L4DC (2021)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Iterative Pre-Conditioning to Expedite the Gradient-Descent Method. ACC (2020)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Iterative Pre-Conditioning for Expediting the Gradient-Descent Method: The Distributed Linear Least-Squares Problem. CoRR (2020)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Iterative Pre-Conditioning to Expedite the Gradient-Descent Method. CoRR (2020)
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
Accelerating Distributed SGD for Linear Linear Regression using Iterative Pre-Conditioning. CoRR (2020)