Arun Jambulapati

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 58

Top Topics

Convex Optimization

Semidefinite Program

Generalized Linear Models

Top Venues

Publications

Jose H. Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
Towards optimal running timesfor optimal transport. Oper. Res. Lett. 52 (2024)
Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
Sparsifying Generalized Linear Models. STOC (2024)
Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
Black-Box k-to-1-PCA Reductions: Theory and Applications. COLT (2024)
Arun Jambulapati, Aaron Sidford, Kevin Tian
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. COLT (2024)
Arun Jambulapati, Aaron Sidford, Kevin Tian
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. CoRR (2024)
Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions. SODA (2024)
Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
Black-Box k-to-1-PCA Reductions: Theory and Applications. CoRR (2024)
Arun Jambulapati, Victor Reis, Kevin Tian
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. SODA (2024)
Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
Sparsifying generalized linear models. CoRR (2023)
Arun Jambulapati, Kevin Tian
Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations. NeurIPS (2023)
Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
ReSQueing Parallel and Private Stochastic Convex Optimization. CoRR (2023)
Arun Jambulapati, Victor Reis, Kevin Tian
Linear-Sized Sparsifiers via Near-Linear Time Discrepancy Theory. CoRR (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS (2023)
Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions. CoRR (2023)
Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
Sparsifying Sums of Norms. CoRR (2023)
Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford
Sparsifying Sums of Norms. FOCS (2023)
Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian
ReSQueing Parallel and Private Stochastic Convex Optimization. FOCS (2023)
Arun Jambulapati, Yang P. Liu, Aaron Sidford
Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification. STOC (2023)
Arun Jambulapati, Hilaf Hasson, Youngsuk Park, Yuyang Wang
Testing Causality for High Dimensional Data. CoRR (2023)
Arun Jambulapati, Yin Tat Lee, Santosh S. Vempala
A Slightly Improved Bound for the KLS Constant. CoRR (2022)
Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford
Optimal and Adaptive Monteiro-Svaiter Acceleration. CoRR (2022)
Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space. SODA (2022)
Arun Jambulapati, Yang P. Liu, Aaron Sidford
-norm regression. STOC (2022)
Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization. CoRR (2022)
Arun Jambulapati, Yang P. Liu, Aaron Sidford
Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification. CoRR (2022)
Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford
Optimal and Adaptive Monteiro-Svaiter Acceleration. NeurIPS (2022)
Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. ICALP (2022)
Jan van den Brand, Yu Gao, Arun Jambulapati, Yin Tat Lee, Yang P. Liu, Richard Peng, Aaron Sidford
Faster maxflow via improved dynamic spectral vertex sparsifiers. STOC (2022)
Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization. ICML (2022)
Deeksha Adil, Brian Bullins, Arun Jambulapati, Sushant Sachdeva
Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities. CoRR (2022)
Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian
Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. CoRR (2022)
Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
Stochastic Bias-Reduced Gradient Methods. CoRR (2021)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. CoRR (2021)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. NeurIPS (2021)
Arun Jambulapati, Aaron Sidford
Ultrasparse Ultrasparsifiers and Faster Laplacian System Solvers. SODA (2021)
Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss. COLT (2021)
Arun Jambulapati, Yang P. Liu, Aaron Sidford
Improved Iteration Complexities for Overconstrained p-Norm Regression. CoRR (2021)
Jan van den Brand, Yu Gao, Arun Jambulapati, Yin Tat Lee, Yang P. Liu, Richard Peng, Aaron Sidford
Faster Maxflow via Improved Dynamic Spectral Vertex Sparsifiers. CoRR (2021)
Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
Stochastic Bias-Reduced Gradient Methods. NeurIPS (2021)
Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss. CoRR (2021)
Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
Acceleration with a Ball Optimization Oracle. NeurIPS (2020)
Arun Jambulapati, Jerry Li, Kevin Tian
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. CoRR (2020)
Arun Jambulapati, Jerry Li, Kevin Tian
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. NeurIPS (2020)
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent. CoRR (2020)
Arun Jambulapati, Aaron Sidford
Ultrasparse Ultrasparsifiers and Faster Laplacian System Solvers. CoRR (2020)
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
Positive semidefinite programming: mixed, parallel, and width-independent. STOC (2020)
Yair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
Acceleration with a Ball Optimization Oracle. CoRR (2020)
Yang P. Liu, Arun Jambulapati, Aaron Sidford
Parallel Reachability in Almost Linear Work and Square Root Depth. FOCS (2019)
Arun Jambulapati, Aaron Sidford, Kevin Tian
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport. NeurIPS (2019)
Arun Jambulapati, Yang P. Liu, Aaron Sidford
Parallel Reachability in Almost Linear Work and Square Root Depth. CoRR (2019)
Arun Jambulapati, Aaron Sidford, Kevin Tian
A Direct Õ(1/ε) Iteration Parallel Algorithm for Optimal Transport. CoRR (2019)
AmirMahdi Ahmadinejad, Arun Jambulapati, Amin Saberi, Aaron Sidford
Perron-Frobenius Theory in Nearly Linear Time: Positive Eigenvectors, M-matrices, Graph Kernels, and Other Applications. SODA (2019)
AmirMahdi Ahmadinejad, Arun Jambulapati, Amin Saberi, Aaron Sidford
Perron-Frobenius Theory in Nearly Linear Time: Positive Eigenvectors, M-matrices, Graph Kernels, and Other Applications. CoRR (2018)
Arun Jambulapati, Kirankumar Shiragur, Aaron Sidford
Efficient Structured Matrix Recovery and Nearly-Linear Time Algorithms for Solving Inverse Symmetric M-Matrices. CoRR (2018)
Arun Jambulapati, Aaron Sidford
) Spectral Sketches for the Laplacian and its Pseudoinverse. SODA (2018)
Jose H. Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
Towards Optimal Running Times for Optimal Transport. CoRR (2018)
Arun Jambulapati, Aaron Sidford
Efficient Õ(n/ε) Spectral Sketches for the Laplacian and its Pseudoinverse. CoRR (2017)