default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKushal Chakrabarti
Person information
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[j5]Kushal Chakrabarti, Nikhil Chopra:
A control theoretic framework for adaptive gradient optimizers. Autom. 160: 111466 (2024)- [j4]Kushal Chakrabarti
, Nikhil Chopra:
On Convergence of the Iteratively Preconditioned Gradient-Descent (IPG) Observer. IEEE Control. Syst. Lett. 8: 1715-1720 (2024) - [c10]Kushal Chakrabarti, Mayank Baranwal:
A Methodology Establishing Linear Convergence of Adaptive Gradient Methods under PL Inequality. ECAI 2024: 2402-2409 - [i12]Kushal Chakrabarti, Nikhil Chopra:
On Convergence of the Iteratively Preconditioned Gradient-Descent (IPG) Observer. CoRR abs/2405.09137 (2024) - [i11]Kushal Chakrabarti, Mayank Baranwal:
A Methodology Establishing Linear Convergence of Adaptive Gradient Methods under PL Inequality. CoRR abs/2407.12629 (2024) - [i10]Mayank Baranwal, Kushal Chakrabarti:
Distributed Optimization via Energy Conservation Laws in Dilated Coordinates. CoRR abs/2409.19279 (2024) - 2023
- [c9]Kushal Chakrabarti, Nikhil Chopra:
IPG Observer: A Newton-Type Observer Robust to Measurement Noise. ACC 2023: 3069-3074 - [c8]Tianchen Liu, Kushal Chakrabarti, Nikhil Chopra:
Iteratively Preconditioned Gradient-Descent Approach for Moving Horizon Estimation Problems. CDC 2023: 8457-8462 - [c7]Dhruv Srinivasan, Kushal Chakrabarti, Nikhil Chopra, Avik Dutt:
Quantum Circuit Optimization through Iteratively Pre-Conditioned Gradient Descent. QCE 2023: 443-449 - [i9]Tianchen Liu, Kushal Chakrabarti, Nikhil Chopra:
Iteratively Preconditioned Gradient-Descent Approach for Moving Horizon Estimation Problems. CoRR abs/2306.13194 (2023) - [i8]Kushal Chakrabarti, Mayank Baranwal:
Linear Convergence of Pre-Conditioned PI Consensus Algorithm under Restricted Strong Convexity. CoRR abs/2310.00419 (2023) - 2022
- [j3]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: 110095 (2022) - [j2]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): 811-822 (2022) - [c6]Kushal Chakrabarti, Amrit S. Bedi, Fikadu T. Dagefu, Jeffrey N. Twigg, Nikhil Chopra:
Fast Distributed Beamforming without Receiver Feedback. IEEECONF 2022: 1408-1412 - [c5]Kushal Chakrabarti, Nikhil Chopra:
Analysis and Synthesis of Adaptive Gradient Algorithms in Machine Learning: The Case of AdaBound and MAdamSSM. CDC 2022: 795-800 - [i7]Kushal Chakrabarti, Nikhil Chopra:
A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning. CoRR abs/2206.02034 (2022) - 2021
- [j1]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): 2180-2185 (2021) - [c4]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. ACC 2021: 2248-2253 - [c3]Kushal Chakrabarti, Nikhil Chopra:
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective. CDC 2021: 1496-1501 - [c2]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning. L4DC 2021: 447-458 - [i6]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. CoRR abs/2101.10967 (2021) - [i5]Kushal Chakrabarti, Nikhil Chopra:
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective. CoRR abs/2106.00092 (2021) - [i4]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
On Accelerating Distributed Convex Optimizations. CoRR abs/2108.08670 (2021) - 2020
- [c1]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Iterative Pre-Conditioning to Expedite the Gradient-Descent Method. ACC 2020: 3977-3982 - [i3]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Iterative Pre-Conditioning to Expedite the Gradient-Descent Method. CoRR abs/2003.07180 (2020) - [i2]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Iterative Pre-Conditioning for Expediting the Gradient-Descent Method: The Distributed Linear Least-Squares Problem. CoRR abs/2008.02856 (2020) - [i1]Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Accelerating Distributed SGD for Linear Linear Regression using Iterative Pre-Conditioning. CoRR abs/2011.07595 (2020)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-28 20:15 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
