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ORCIDVishwak Srinivasan
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Conference and Workshop Papers
- 2024
[c5]Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson:
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm. COLT 2024: 4593-4635- 2021
- [c4]Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li:
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity. ICML 2021: 7412-7422 - [c3]Vishwak Srinivasan, Justin Khim, Arindam Banerjee, Pradeep Ravikumar:
Subseasonal climate prediction in the western US using Bayesian spatial models. UAI 2021: 961-970 - 2020
- [c2]Adarsh Prasad, Vishwak Srinivasan, Sivaraman Balakrishnan, Pradeep Ravikumar:
On Learning Ising Models under Huber's Contamination Model. NeurIPS 2020 - 2018
- [c1]Vishwak Srinivasan, Adepu Ravi Sankar, Vineeth N. Balasubramanian
:
ADINE: an adaptive momentum method for stochastic gradient descent. COMAD/CODS 2018: 249-256
Informal and Other Publications
- 2023
- [i4]Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson:
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin Algorithm. CoRR abs/2312.08823 (2023) - 2021
- [i3]Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li:
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity. CoRR abs/2106.07814 (2021) - 2018
- [i2]Adepu Ravi Sankar, Vishwak Srinivasan, Vineeth N. Balasubramanian:
On the Analysis of Trajectories of Gradient Descent in the Optimization of Deep Neural Networks. CoRR abs/1807.08140 (2018) - 2017
- [i1]Vishwak Srinivasan, Adepu Ravi Sankar, Vineeth N. Balasubramanian:
ADINE: An Adaptive Momentum Method for Stochastic Gradient Descent. CoRR abs/1712.07424 (2017)
Coauthor Index
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