Siddharth Mitra
I'm a PhD student in Computer Science at Yale University, where I'm lucky to be advised by Andre Wibisono.
I'm broadly interested in sampling, optimization, and information theory.
Prior to this, I was an undergraduate and masters student at the Chennai Mathematical Institute (while also spending some time at the Indian Institute of Science, Bangalore) where I worked with Aditya Gopalan, Himanshu Tyagi, and KV Subrahmanyam.
I can be reached at siddharth.mitra <at> yale <dot> edu.
My Google Scholar.
Publications
Fast Convergence of Φ-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler [arXiv]
(α-β) Siddharth Mitra and Andre Wibisono
On Independent Samples Along the Langevin Diffusion and the Unadjusted Langevin Algorithm [arXiv]
(α-β) Jiaming Liang, Siddharth Mitra, and Andre Wibisono
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning [arXiv]
(α-β) Amin Karbasi, Nikki Kuang, Yian Ma, and Siddharth Mitra
ICML 2023.
Submodular + Concave [arXiv]
Siddharth Mitra, Moran Feldman, and Amin Karbasi
NeurIPS 2021.
On Adaptivity in Information-constrained Online Learning [arXiv]
Siddharth Mitra and Aditya Gopalan
AAAI 2020. Short version at
OPT 2019 [OPT Poster].