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ORCIDRohan Deb
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2020 – today
- 2024
[c5]Rohan Deb, Aadirupa Saha, Arindam Banerjee:
Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources. AISTATS 2024: 4546-4554- [c4]Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee:
Contextual Bandits with Online Neural Regression. ICLR 2024 - 2023
- [c3]Swetha Ganesh, Rohan Deb, Gugan Thoppe, Amarjit Budhiraja:
Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis. UAI 2023: 602-612 - [i6]Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee:
Contextual Bandits with Online Neural Regression. CoRR abs/2312.07145 (2023) - [i5]Rohan Deb, Aadirupa Saha:
Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources. CoRR abs/2312.17229 (2023) - 2022
- [c2]Rohan Deb, Shalabh Bhatnagar:
Gradient Temporal Difference with Momentum: Stability and Convergence. AAAI 2022: 6488-6496 - [c1]Rohan Deb, Meet Gandhi, Shalabh Bhatnagar:
Schedule Based Temporal Difference Algorithms. Allerton 2022: 1-6 - 2021
- [i4]Gugan Thoppe, Rohan Deb, Swetha Ganesh, Amarjit Budhiraja:
Does Momentum Help? A Sample Complexity Analysis. CoRR abs/2110.15547 (2021) - [i3]Rohan Deb, Shalabh Bhatnagar:
Gradient Temporal Difference with Momentum: Stability and Convergence. CoRR abs/2111.11004 (2021) - [i2]Rohan Deb, Meet Gandhi, Shalabh Bhatnagar:
Schedule Based Temporal Difference Algorithms. CoRR abs/2111.11768 (2021) - [i1]Rohan Deb, Shalabh Bhatnagar:
N-Timescale Stochastic Approximation: Stability and Convergence. CoRR abs/2112.03515 (2021)
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