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Karan N. Chadha
Observed names:
Chadha, Karan,
Karan Chadha
Observed institutions:
Indian Institute of Technology Bombay,
Stanford University
OpenAlex ID:
A5063754276
Fine-tuning is Fine in Federated Learning
2021
·
Gary Cheng
, Karan N. Chadha
, et al.
·
arXiv (Cornell University)
·
15
A reinforcement learning algorithm for restless bandits
2018
·
Vivek S. Borkar
, Karan Chadha
·
Indian Control Conference
·
14
Differentially Private Heavy Hitter Detection using Federated Analytics
2024
·
Karan Chadha
, Junye Chen
, et al.
·
IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
·
10
PDF
Federated Asymptotics: a model to compare federated learning algorithms
2021
·
Cheng, Gary
, Chadha, Karan
, et al.
·
arXiv (Cornell University)
·
6
PDF
Minibatch Stochastic Approximate Proximal Point Methods
2020
·
Hilal Asi
, Karan N. Chadha
, et al.
·
neural information processing systems
·
5
Efficiency fairness tradeoff in battery sharing
2021
·
Karan N. Chadha
, Ankur A. Kulkarni
, et al.
·
Operations Research Letters
·
4
PDF
Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization
2021
·
Chadha, Karan
, Cheng, Gary
, et al.
·
arXiv (Cornell University)
·
4
PDF
On independent cliques and linear complementarity problems
2022
·
Karan N. Chadha
, Ankur A. Kulkarni
·
Indian Journal of Pure and Applied Mathematics
·
3
PDF
Aggregate play and welfare in strategic interactions on networks
2020
·
Karan N. Chadha
, Ankur A. Kulkarni
·
Journal of Mathematical Economics
·
3
PDF
Auditing Private Prediction
2024
·
Chadha, Karan
, Jagielski, Matthew
, et al.
·
arXiv (Cornell University)
·
2
PDF
Resampling methods for private statistical inference
2024
·
Chadha, Karan
, Duchi, John
, et al.
·
arXiv (Cornell University)
·
1
PDF
Private optimization in the interpolation regime: faster rates and hardness results
2022
·
Asi, Hilal
, Chadha, Karan
, et al.
·
arXiv (Cornell University)
·
1
PDF
Memorization Dynamics in Knowledge Distillation for Language Models
2026
·
Borkar, Jaydeep
, Chadha, Karan
, et al.
·
arXiv (Cornell University)
PDF
Fine-tuning in Federated Learning: a simple but tough-to-beat baseline.
2021
·
Gary Cheng
, Karan N. Chadha
, et al.
·
arXiv (Cornell University)
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Works count:
15
Citation count:
68
H-index:
5
I10-index:
3
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