Dheeraj Baby
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I am a final year PhD student in Computer Science department at UC Santa Barbara where I am fortunate to be advised by Prof. Yu-Xiang Wang. My research primarily focuses on developing online learning algorithms that can optimally cope with non-stationarities present in the environment. Applications of my work include forecasting trends in Time Series, adaptive Total Variation denoising, non-stationary Multi Armed Bandits, Online Convex Optimization… I received my Bachelors and Masters degrees in Electrical Engineering from Indian Institue of Technology, Chennai during 2016.
Publications
Dheeraj Baby*, Saurabh Garg*, Tzu-Ching Yen*, Sivaraman Balakrishnan, Zachary Lipton and Yu-Xiang Wang "Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms", NeurIPS 2023 [pdf], Spotlight Presentation
Soumyabrata Pal and Dheeraj Baby "Online Matrix Completion: A Collaborative Approach with Hott Items", Under review 2023
Dheeraj Baby and Yu-Xiang Wang "Second Order Path Variationals in Non-Stationary Online Learning", AISTATS 2023 [pdf]
Dheeraj Baby, Aniket Das, Dheeraj Nagaraj and Praneeth Netrapalli, "Near Optimal Heteroscedastic Regression with Symbiotic Learning", COLT 2023 [pdf]
Dheeraj Baby*, Jianyu Xu* and Yu-Xiang Wang "Non-stationary Contextual Pricing with Safety Constraints", TMLR 2022
Dheeraj Baby and Yu-Xiang Wang "Optimal Dynamic Regret in LQR Control", NeurIPS 2022 [pdf]
Dheeraj Baby and Yu-Xiang Wang "Optimal Dynamic Regret in Proper Online Learning with Strongly Convex Losses and Beyond", AISTATS 2022 [pdf]
Dheeraj Baby and Yu-Xiang Wang "Optimal Dynamic Regret in Exp-Concave Online Learning", COLT 2021 [pdf], Best Student Paper Award
Dheeraj Baby, Xuandong Zhao and Yu-Xiang Wang "An Optimal Reduction of TV-Denoising to Adaptive Online Learning", AISTATS 2021 [pdf]
Dheeraj Baby and Yu-Xiang Wang "Adaptive Online Estimation of Piecewise Polynomial Trends", NeurIPS 2020 [pdf]
Dheeraj Baby and Yu-Xiang Wang "Online Forecasting of Total-Variation-Bounded Sequences", NeurIPS 2019 [pdf] [video]
Jason R. Baumgartner, Robert L. Kanzelman, Pradeep Kumar Nalla, Raj Kumar Gajavelly, Dheeraj Baby "Initial-state and next-state value folding", US Patent [US10621297B1]
(* = Equal contribution)
Industry and Academic Experience
Reviewer at ICML19,20,21,23 JMLR21,22,23 AISTATS22,23, ICLR24
Intern, AWS AI Labs, AWS Deep Engine Science, Aug 2023 - Nov 2023
Intern, Google Research, Machine Learning and Optimization group, Jun 2022 - Sept 2022
Intern, AWS AI Labs, Time Series forecasting group, Jun 2020 - Sept 2020
Software developer, IBM Bangalore, India, 2016-2018