Arun Jambulapati

68 papers A* 30A 1Journal 37

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Expander Decomposition with Almost Optimal Overhead. CoRR Nikhil Bansal, Arun Jambulapati, Thatchaphol Saranurak
2025	A*	`conf`	Eulerian Graph Sparsification by Effective Resistance Decomposition. SODA Arun Jambulapati, Sushant Sachdeva, Aaron Sidford, Kevin Tian, Yibin Zhao
2025	A	`conf`	Extracting Dual Solutions via Primal Optimizers. ITCS Yair Carmon, Arun Jambulapati, Liam O'Carroll, Aaron Sidford
2025	A*	`conf`	Radial Isotropic Position via an Implicit Newton's Method. FOCS Arun Jambulapati, Jonathan Li, Kevin Tian
2025	J	`jnl`	Radial Isotropic Position via an Implicit Newton's Method. CoRR Arun Jambulapati, Jonathan Li, Kevin Tian
2025	J	`jnl`	Ultrasparse Ultrasparsifiers and Faster Laplacian System Solvers. ACM Trans. Algorithms Arun Jambulapati, Aaron Sidford
2024	A*	`conf`	A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions. SODA Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2024	A*	`conf`	Black-Box k-to-1-PCA Reductions: Theory and Applications. COLT Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
2024	J	`jnl`	Black-Box k-to-1-PCA Reductions: Theory and Applications. CoRR Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
2024	A*	`conf`	Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. COLT Arun Jambulapati, Aaron Sidford, Kevin Tian
2024	J	`jnl`	Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. CoRR Arun Jambulapati, Aaron Sidford, Kevin Tian
2024	J	`jnl`	Convex optimization with CoRR Deeksha Adil, Brian Bullins, Arun Jambulapati, Aaron Sidford
2024	J	`jnl`	Eulerian Graph Sparsification by Effective Resistance Decomposition. CoRR Arun Jambulapati, Sushant Sachdeva, Aaron Sidford, Kevin Tian, Yibin Zhao
2024	J	`jnl`	Extracting Dual Solutions via Primal Optimizers. CoRR Yair Carmon, Arun Jambulapati, Liam O'Carroll, Aaron Sidford
2024	A*	`conf`	Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. SODA Arun Jambulapati, Victor Reis, Kevin Tian
2024	A*	`conf`	Sparsifying Generalized Linear Models. STOC Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
2024	A*	`conf`	Testing Calibration in Nearly-Linear Time. NeurIPS Lunjia Hu, Arun Jambulapati, Kevin Tian, Chutong Yang
2024	J	`jnl`	Towards optimal running timesfor optimal transport. Oper. Res. Lett. Jose H. Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
2023	J	`jnl`	A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions. CoRR Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2023	A*	`conf`	Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification. STOC Arun Jambulapati, Yang P. Liu, Aaron Sidford
2023	J	`jnl`	Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. CoRR Arun Jambulapati, Victor Reis, Kevin Tian
2023	A*	`conf`	ReSQueing Parallel and Private Stochastic Convex Optimization. FOCS Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
2023	J	`jnl`	ReSQueing Parallel and Private Stochastic Convex Optimization. CoRR Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
2023	A*	`conf`	Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations. NeurIPS Arun Jambulapati, Kevin Tian
2023	A*	`conf`	Sparsifying Sums of Norms. FOCS Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
2023	J	`jnl`	Sparsifying Sums of Norms. CoRR Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
2023	J	`jnl`	Sparsifying generalized linear models. CoRR Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
2023	A*	`conf`	Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2023	J	`jnl`	Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2023	J	`jnl`	Testing Causality for High Dimensional Data. CoRR Arun Jambulapati, Hilaf Hasson, Youngsuk Park, Yuyang Wang
2022	J	`jnl`	A Slightly Improved Bound for the KLS Constant. CoRR Arun Jambulapati, Yin Tat Lee, Santosh S. Vempala
2022	J	`jnl`	Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification. CoRR Arun Jambulapati, Yang P. Liu, Aaron Sidford
2022	A*	`conf`	Faster maxflow via improved dynamic spectral vertex sparsifiers. STOC Jan van den Brand, Yu Gao, Arun Jambulapati, Yin Tat Lee, Yang P. Liu, Richard Peng, Aaron Sidford
2022	A*	`conf`	Improved iteration complexities for overconstrained STOC Arun Jambulapati, Yang P. Liu, Aaron Sidford
2022	J	`jnl`	Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities. CoRR Deeksha Adil, Brian Bullins, Arun Jambulapati, Sushant Sachdeva
2022	A*	`conf`	Optimal and Adaptive Monteiro-Svaiter Acceleration. NeurIPS Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford
2022	J	`jnl`	Optimal and Adaptive Monteiro-Svaiter Acceleration. CoRR Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford
2022	A*	`conf`	RECAPP: Crafting a More Efficient Catalyst for Convex Optimization. ICML Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2022	J	`jnl`	RECAPP: Crafting a More Efficient Catalyst for Convex Optimization. CoRR Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2022	A*	`conf`	Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. ICALP Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
2022	J	`jnl`	Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. CoRR Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
2022	A*	`conf`	Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space. SODA Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
2021	J	`jnl`	Faster Maxflow via Improved Dynamic Spectral Vertex Sparsifiers. CoRR Jan van den Brand, Yu Gao, Arun Jambulapati, Yin Tat Lee, Yang P. Liu, Richard Peng, Aaron Sidford
2021	J	`jnl`	Improved Iteration Complexities for Overconstrained p-Norm Regression. CoRR Arun Jambulapati, Yang P. Liu, Aaron Sidford
2021	A*	`conf`	Robust Regression Revisited: Acceleration and Improved Estimation Rates. NeurIPS Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
2021	J	`jnl`	Robust Regression Revisited: Acceleration and Improved Estimation Rates. CoRR Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
2021	A*	`conf`	Stochastic Bias-Reduced Gradient Methods. NeurIPS Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2021	J	`jnl`	Stochastic Bias-Reduced Gradient Methods. CoRR Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2021	A*	`conf`	Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss. COLT Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2021	J	`jnl`	Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss. CoRR Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
2021	A*	`conf`	Ultrasparse Ultrasparsifiers and Faster Laplacian System Solvers. SODA Arun Jambulapati, Aaron Sidford
2020	A*	`conf`	Acceleration with a Ball Optimization Oracle. NeurIPS Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
2020	J	`jnl`	Acceleration with a Ball Optimization Oracle. CoRR Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
2020	J	`jnl`	Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent. CoRR Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
2020	A*	`conf`	Positive semidefinite programming: mixed, parallel, and width-independent. STOC Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
2020	A*	`conf`	Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. NeurIPS Arun Jambulapati, Jerry Li, Kevin Tian
2020	J	`jnl`	Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. CoRR Arun Jambulapati, Jerry Li, Kevin Tian
2020	J	`jnl`	Ultrasparse Ultrasparsifiers and Faster Laplacian System Solvers. CoRR Arun Jambulapati, Aaron Sidford
2019	J	`jnl`	A Direct Õ(1/ε) Iteration Parallel Algorithm for Optimal Transport. CoRR Arun Jambulapati, Aaron Sidford, Kevin Tian
2019	A*	`conf`	A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport. NeurIPS Arun Jambulapati, Aaron Sidford, Kevin Tian
2019	A*	`conf`	Parallel Reachability in Almost Linear Work and Square Root Depth. FOCS Yang P. Liu, Arun Jambulapati, Aaron Sidford
2019	J	`jnl`	Parallel Reachability in Almost Linear Work and Square Root Depth. CoRR Arun Jambulapati, Yang P. Liu, Aaron Sidford
2019	A*	`conf`	Perron-Frobenius Theory in Nearly Linear Time: Positive Eigenvectors, M-matrices, Graph Kernels, and Other Applications. SODA AmirMahdi Ahmadinejad, Arun Jambulapati, Amin Saberi, Aaron Sidford
2018	A*	`conf`	Efficient SODA Arun Jambulapati, Aaron Sidford
2018	J	`jnl`	Efficient Structured Matrix Recovery and Nearly-Linear Time Algorithms for Solving Inverse Symmetric M-Matrices. CoRR Arun Jambulapati, Kirankumar Shiragur, Aaron Sidford
2018	J	`jnl`	Perron-Frobenius Theory in Nearly Linear Time: Positive Eigenvectors, M-matrices, Graph Kernels, and Other Applications. CoRR AmirMahdi Ahmadinejad, Arun Jambulapati, Amin Saberi, Aaron Sidford
2018	J	`jnl`	Towards Optimal Running Times for Optimal Transport. CoRR Jose H. Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
2017	J	`jnl`	Efficient Õ(n/ε) Spectral Sketches for the Laplacian and its Pseudoinverse. CoRR Arun Jambulapati, Aaron Sidford