Senior Researcher
Bloomberg AI
cgupta61@bloomberg.net
I am now at Bloomberg AI in New York! Please reach out if you’d like to know more about what we do.
Previously, I spent five wonderful years at Carnegie Mellon University, where I obtained a PhD in Machine Learning under the guidance of Aaditya Ramdas. My research was awarded the Bloomberg Data Science Fellowship. My PhD dissertation, titled “Post-hoc calibration without distributional assumptions”, can be found here. Earlier, I was a Research Fellow at Microsoft Research, India with Prateek Jain. I did my undergrad (B. Tech) in Computer Science at IIT Kanpur.
(in reverse chronological order of first preprint)
Parity Calibration
Youngseog Chung, Aaron Rumack, Chirag Gupta
UAI 2023 (oral). [arxiv]
Online Platt Scaling with Calibeating
Chirag Gupta, Aaditya Ramdas
ICML 2023. [arxiv]
Faster online calibration without randomization: interval forecasts and the power of two choices
Chirag Gupta, Aaditya Ramdas
COLT 2022. [proc] [arxiv]
Top-label calibration and multiclass-to-binary reductions
Chirag Gupta, Aaditya Ramdas
ICLR 2022. [proc] [arxiv] [code]
Distribution-free calibration guarantees for histogram binning without sample splitting
Chirag Gupta, Aaditya Ramdas
ICML 2021.
[arxiv] [proc] [code] [talk (from 37’ to 50’)]
Distribution-free binary classification: prediction sets, confidence intervals and calibration
Chirag Gupta*, Aleksandr Podkopaev*, Aaditya Ramdas
Neurips 2020 (spotlight).
[arxiv] [proc] [talk (from 24’ to 38’)]
Nested conformal prediction and quantile out-of-bag ensemble methods
Chirag Gupta, Arun K Kuchibhotla, Aaditya Ramdas
Pattern Recognition (Special Issue on Conformal Prediction) 2022.
[journal] [arxiv] [code] [talk (from 3’ to 24’)]
Path length bounds for gradient descent and flow
Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas
Journal of Machine Learning Research (JMLR) 2021.
[journal] [arxiv] [blog]
Support recovery for orthogonal matching pursuit: upper and lower bounds
Raghav Somani*, Chirag Gupta*, Prateek Jain, Praneeth Netrapalli
Neurips 2018 (spotlight).
[proc]
Protonn: Compressed and accurate knn for resource-scarce devices
Chirag Gupta, Arun Sai Suggala, Ankit Goyal, Harsha Vardhan Simhadri, Bhargavi Paranjape, Ashish Kumar, Saurabh Goyal, Raghavendra Udupa, Manik Varma, Prateek Jain
ICML 2017.
[proc] [code]
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