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Author search results
Likely matches
- Suvrit Sra
Massachusetts Institute of Technology (MIT), Laboratory for Information and Decision Systems, Cambridge, MA, USA
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Publication search results
found 205 matches
- 2024
- Xiang Cheng, Jingzhao Zhang, Suvrit Sra:
Efficient Sampling on Riemannian Manifolds via Langevin MCMC. CoRR abs/2402.10357 (2024) - 2023
- Melanie Weber, Suvrit Sra:
Riemannian Optimization via Frank-Wolfe Methods. Math. Program. 199(1): 525-556 (2023) - Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra:
Sion's Minimax Theorem in Geodesic Metric Spaces and a Riemannian Extragradient Algorithm. SIAM J. Optim. 33(4): 2885-2908 (2023) - Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra:
Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control. CDC 2023: 6166-6171 - Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka:
Sign and Basis Invariant Networks for Spectral Graph Representation Learning. ICLR 2023 - Melanie Weber, Suvrit Sra:
Global optimality for Euclidean CCCP under Riemannian convexity. ICML 2023: 36790-36803 - David Xing Wu, Chulhee Yun, Suvrit Sra:
On the Training Instability of Shuffling SGD with Batch Normalization. ICML 2023: 37787-37845 - Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra:
Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? L4DC 2023: 51-63 - Yan Dai, Kwangjun Ahn, Suvrit Sra:
The Crucial Role of Normalization in Sharpness-Aware Minimization. NeurIPS 2023 - Kwangjun Ahn, Xiang Cheng, Hadi Daneshmand, Suvrit Sra:
Transformers learn to implement preconditioned gradient descent for in-context learning. NeurIPS 2023 - David Xing Wu, Chulhee Yun, Suvrit Sra:
On the Training Instability of Shuffling SGD with Batch Normalization. CoRR abs/2302.12444 (2023) - Yan Dai, Kwangjun Ahn, Suvrit Sra:
The Crucial Role of Normalization in Sharpness-Aware Minimization. CoRR abs/2305.15287 (2023) - Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra:
How to escape sharp minima. CoRR abs/2305.15659 (2023) - Kwangjun Ahn, Xiang Cheng, Hadi Daneshmand, Suvrit Sra:
Transformers learn to implement preconditioned gradient descent for in-context learning. CoRR abs/2306.00297 (2023) - Adarsh Barik, Suvrit Sra, Jean Honorio:
Invex Programs: First Order Algorithms and Their Convergence. CoRR abs/2307.04456 (2023) - Kwangjun Ahn, Xiang Cheng, Minhak Song, Chulhee Yun, Ali Jadbabaie, Suvrit Sra:
Linear attention is (maybe) all you need (to understand transformer optimization). CoRR abs/2310.01082 (2023) - Xiang Cheng, Yuxin Chen, Suvrit Sra:
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context. CoRR abs/2312.06528 (2023) - 2022
- Anshul Shah, Suvrit Sra, Rama Chellappa, Anoop Cherian:
Max-Margin Contrastive Learning. AAAI 2022: 8220-8230 - Jikai Jin, Suvrit Sra:
Understanding Riemannian Acceleration via a Proximal Extragradient Framework. COLT 2022: 2924-2962 - Chulhee Yun, Shashank Rajput, Suvrit Sra:
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond. ICLR 2022 - Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra:
Understanding the unstable convergence of gradient descent. ICML 2022: 247-257 - Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie:
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity. ICML 2022: 26347-26361 - Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie:
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective. ICML 2022: 26330-26346 - Horia Mania, Ali Jadbabaie, Devavrat Shah, Suvrit Sra:
Time Varying Regression with Hidden Linear Dynamics. L4DC 2022: 858-869 - Xiang Cheng, Jingzhao Zhang, Suvrit Sra:
Efficient Sampling on Riemannian Manifolds via Langevin MCMC. NeurIPS 2022 - Alp Yurtsever, Suvrit Sra:
CCCP is Frank-Wolfe in disguise. NeurIPS 2022 - Kwangjun Ahn, Suvrit Sra:
Understanding Nesterov's Acceleration via Proximal Point Method. SOSA 2022: 117-130 - Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra:
Minimax in Geodesic Metric Spaces: Sion's Theorem and Algorithms. CoRR abs/2202.06950 (2022) - Derek Lim, Joshua Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka:
Sign and Basis Invariant Networks for Spectral Graph Representation Learning. CoRR abs/2202.13013 (2022) - Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra:
Understanding the unstable convergence of gradient descent. CoRR abs/2204.01050 (2022)
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