| 2026 | COLT | Randomization for Faster Exact Optimization of Discounted Markov Decision Processes. | Andrei Graur, Aaron Sidford, Ta-Wei Tu |
| 2026 | COLT | Computing Lewis weights to high precision using local relative smoothness. | Sander Gribling, Aaron Sidford, Chenyi Zhang |
| 2026 | COLT | Fast, Parallel, Query-Efficient Binary Classification. | Ishani Karmarkar, Liam O'Carroll, Aaron Sidford |
| 2026 | SODA | From Incremental Transitive Cover to Strongly Polynomial Maximum Flow. | Daniel Dadush, James B. Orlin, Aaron Sidford, Lszl A. Vgh |
| 2026 | SODA | Approaching Optimality for Solving Dense Linear Systems with Low-Rank Structure. | Michal Derezinski, Aaron Sidford |
| 2026 | STOC | Solving Matrix Games with Near-Optimal Matvec Complexity. | Ishani Karmarkar, Liam O'Carroll, Aaron Sidford |
| 2025 | FOCS | Generalized Flow in Nearly-linear Time on Moderately Dense Graphs. | Shunhua Jiang, Michael Kapralov, Lawrence Li, Aaron Sidford |
| 2025 | FOCS | Solving Zero-Sum Games with Fewer Matrix-Vector Products. | Ishani Karmarkar, Liam O'Carroll, Aaron Sidford |
| 2025 | SODA | Entropy Regularization and Faster Decremental Matching in General Graphs. | Jiale Chen, Aaron Sidford, Ta-Wei Tu |
| 2025 | SODA | Matching Composition and Efficient Weight Reduction in Dynamic Matching. | Aaron Bernstein, Jiale Chen, Aditi Dudeja, Zachary Langley, Aaron Sidford, Ta-Wei Tu |
| 2025 | SODA | Eulerian Graph Sparsification by Effective Resistance Decomposition. | Arun Jambulapati, Sushant Sachdeva, Aaron Sidford, Kevin Tian, Yibin Zhao |
| 2025 | STOC | Accelerated Approximate Optimization of Multi-commodity Flows on Directed Graphs. | Li Chen, Andrei Graur, Aaron Sidford |
| 2024 | COLT | Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization. | Arun Jambulapati, Aaron Sidford, Kevin Tian |
| 2024 | COLT | Faster Spectral Density Estimation and Sparsification in the Nuclear Norm (Extended Abstract). | Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh |
| 2024 | SODA | Incremental Approximate Maximum Flow on Undirected Graphs in Subpolynomial Update Time. | Jan van den Brand, Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva, Aaron Sidford |
| 2024 | SODA | A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions. | Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford |
| 2024 | STOC | Near-Optimal Dynamic Rounding of Fractional Matchings in Bipartite Graphs. | Sayan Bhattacharya, Peter Kiss, Aaron Sidford, David Wajc |
| 2024 | STOC | Sparsifying Generalized Linear Models. | Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford |
| 2023 | COLT | Moments, Random Walks, and Limits for Spectrum Approximation. | Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh |
| 2023 | COLT | Semi-Random Sparse Recovery in Nearly-Linear Time. | Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian |
| 2023 | FOCS | Singular Value Approximation and Sparsifying Random Walks on Directed Graphs. | AmirMahdi Ahmadinejad, John Peebles, Edward Pyne, Aaron Sidford, Salil P. Vadhan |
| 2023 | FOCS | A Deterministic Almost-Linear Time Algorithm for Minimum-Cost Flow. | Jan van den Brand, Li Chen, Richard Peng, Rasmus Kyng, Yang P. Liu, Maximilian Probst Gutenberg, Sushant Sachdeva, Aaron Sidford |
| 2023 | FOCS | ReSQueing Parallel and Private Stochastic Convex Optimization. | Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian |
| 2023 | FOCS | Sparse Submodular Function Minimization. | Andrei Graur, Haotian Jiang, Aaron Sidford |
| 2023 | FOCS | Sparsifying Sums of Norms. | Arun Jambulapati, James R. Lee, Yang P. Liu, Aaron Sidford |
| 2023 | FOCS | Matrix Completion in Almost-Verification Time. | Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian |
| 2023 | ICML | Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling. | Adam Bouland, Yosheb M. Getachew, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2023 | IJCAI | Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract). | Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant |
| 2023 | SODA | Improved girth approximation in weighted undirected graphs. | Avi Kadria, Liam Roditty, Aaron Sidford, Virginia Vassilevska Williams, Uri Zwick |
| 2023 | STOC | Dynamic Maxflow via Dynamic Interior Point Methods. | Jan van den Brand, Yang P. Liu, Aaron Sidford |
| 2023 | STOC | Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification. | Arun Jambulapati, Yang P. Liu, Aaron Sidford |
| 2022 | COLT | Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods. | Yujia Jin, Aaron Sidford, Kevin Tian |
| 2022 | COLT | Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales. | Jonathan A. Kelner, Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Honglin Yuan |
| 2022 | COLT | Efficient Convex Optimization Requires Superlinear Memory. | Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant |
| 2022 | FOCS | Improved Lower Bounds for Submodular Function Minimization. | Deeparnab Chakrabarty, Andrei Graur, Haotian Jiang, Aaron Sidford |
| 2022 | ICALP | Fully-Dynamic Graph Sparsifiers Against an Adaptive Adversary. | Aaron Bernstein, Jan van den Brand, Maximilian Probst Gutenberg, Danupon Nanongkai, Thatchaphol Saranurak, Aaron Sidford, He Sun |
| 2022 | ICALP | Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching. | Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2022 | ICML | RECAPP: Crafting a More Efficient Catalyst for Convex Optimization. | Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford |
| 2022 | SODA | Semi-Streaming Bipartite Matching in Fewer Passes and Optimal Space. | Sepehr Assadi, Arun Jambulapati, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2022 | SODA | Computing Lewis Weights to High Precision. | Maryam Fazel, Yin Tat Lee, Swati Padmanabhan, Aaron Sidford |
| 2022 | SODA | Algorithmic trade-offs for girth approximation in undirected graphs. | Avi Kadria, Liam Roditty, Aaron Sidford, Virginia Vassilevska Williams, Uri Zwick |
| 2022 | STOC | Faster maxflow via improved dynamic spectral vertex sparsifiers. | Jan van den Brand, Yu Gao, Arun Jambulapati, Yin Tat Lee, Yang P. Liu, Richard Peng, Aaron Sidford |
| 2022 | STOC | Improved iteration complexities for overconstrained | Arun Jambulapati, Yang P. Liu, Aaron Sidford |
| 2021 | COLT | The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. | Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford |
| 2021 | COLT | Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss. | Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford |
| 2021 | ICML | Towards Tight Bounds on the Sample Complexity of Average-reward MDPs. | Yujia Jin, Aaron Sidford |
| 2021 | SODA | Ultrasparse Ultrasparsifiers and Faster Laplacian System Solvers. | Arun Jambulapati, Aaron Sidford |
| 2021 | STOC | Minimum cost flows, MDPs, and ℓ | Jan van den Brand, Yin Tat Lee, Yang P. Liu, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang |
| 2020 | AISTATS | Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity. | Aaron Sidford, Mengdi Wang, Lin Yang, Yinyu Ye |
| 2020 | ALT | Leverage Score Sampling for Faster Accelerated Regression and ERM. | Naman Agarwal, Sham M. Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford |
| 2020 | COLT | Near-Optimal Methods for Minimizing Star-Convex Functions and Beyond. | Oliver Hinder, Aaron Sidford, Nimit Sharad Sohoni |
| 2020 | FOCS | High-precision Estimation of Random Walks in Small Space. | AmirMahdi Ahmadinejad, Jonathan A. Kelner, Jack Murtagh, John Peebles, Aaron Sidford, Salil P. Vadhan |
| 2020 | FOCS | Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs. | Jan van den Brand, Yin Tat Lee, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang |
| 2020 | FOCS | Coordinate Methods for Matrix Games. | Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2020 | FOCS | Unit Capacity Maxflow in Almost $O(m^{4/3})$ Time. | Tarun Kathuria, Yang P. Liu, Aaron Sidford |
| 2020 | ICML | Efficiently Solving MDPs with Stochastic Mirror Descent. | Yujia Jin, Aaron Sidford |
| 2020 | SODA | Near-optimal Approximate Discrete and Continuous Submodular Function Minimization. | Brian Axelrod, Yang P. Liu, Aaron Sidford |
| 2020 | SODA | Fast and Space Efficient Spectral Sparsification in Dynamic Streams. | Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri, Aaron Sidford, Jakab Tardos |
| 2020 | STOC | Solving tall dense linear programs in nearly linear time. | Jan van den Brand, Yin Tat Lee, Aaron Sidford, Zhao Song |
| 2020 | STOC | Constant girth approximation for directed graphs in subquadratic time. | Shiri Chechik, Yang P. Liu, Omer Rotem, Aaron Sidford |
| 2020 | STOC | Faster energy maximization for faster maximum flow. | Yang P. Liu, Aaron Sidford |
| 2019 | COLT | Near-optimal method for highly smooth convex optimization. | Sbastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford |
| 2019 | COLT | A Rank-1 Sketch for Matrix Multiplicative Weights. | Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian |
| 2019 | COLT | Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives. | Alexander V. Gasnikov, Pavel E. Dvurechensky, Eduard Gorbunov, Evgeniya A. Vorontsova, Daniil Selikhanovych, Csar A. Uribe, Bo Jiang, Haoyue Wang, Shuzhong Zhang, Sbastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford |
| 2019 | FOCS | Faster Matroid Intersection. | Deeparnab Chakrabarty, Yin Tat Lee, Aaron Sidford, Sahil Singla, Sam Chiu-wai Wong |
| 2019 | FOCS | Parallel Reachability in Almost Linear Work and Square Root Depth. | Yang P. Liu, Arun Jambulapati, Aaron Sidford |
| 2019 | SODA | Perron-Frobenius Theory in Nearly Linear Time: Positive Eigenvectors, M-matrices, Graph Kernels, and Other Applications. | AmirMahdi Ahmadinejad, Arun Jambulapati, Amin Saberi, Aaron Sidford |
| 2019 | STOC | Efficient profile maximum likelihood for universal symmetric property estimation. | Moses Charikar, Kirankumar Shiragur, Aaron Sidford |
| 2019 | STOC | Memory-sample tradeoffs for linear regression with small error. | Vatsal Sharan, Aaron Sidford, Gregory Valiant |
| 2018 | COLT | Accelerating Stochastic Gradient Descent for Least Squares Regression. | Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford |
| 2018 | COLT | Efficient Convex Optimization with Membership Oracles. | Yin Tat Lee, Aaron Sidford, Santosh S. Vempala |
| 2018 | FOCS | Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. | Michael B. Cohen, Jonathan A. Kelner, Rasmus Kyng, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford |
| 2018 | FOCS | Coordinate Methods for Accelerating ℓ∞ Regression and Faster Approximate Maximum Flow. | Aaron Sidford, Kevin Tian |
| 2018 | SODA | Efficient | Arun Jambulapati, Aaron Sidford |
| 2018 | SODA | Stability of the Lanczos Method for Matrix Function Approximation. | Cameron Musco, Christopher Musco, Aaron Sidford |
| 2018 | SODA | Approximating Cycles in Directed Graphs: Fast Algorithms for Girth and Roundtrip Spanners. | Jakub Pachocki, Liam Roditty, Aaron Sidford, Roei Tov, Virginia Vassilevska Williams |
| 2018 | SODA | Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes. | Aaron Sidford, Mengdi Wang, Xian Wu, Yinyu Ye |
| 2017 | FOCS | Derandomization Beyond Connectivity: Undirected Laplacian Systems in Nearly Logarithmic Space. | Jack Murtagh, Omer Reingold, Aaron Sidford, Salil P. Vadhan |
| 2017 | ICML | "Convex Until Proven Guilty": Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions. | Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford |
| 2017 | STOC | Subquadratic submodular function minimization. | Deeparnab Chakrabarty, Yin Tat Lee, Aaron Sidford, Sam Chiu-wai Wong |
| 2017 | STOC | Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. | Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu |
| 2016 | COLT | Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm. | Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford |
| 2016 | FOCS | Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. | Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu |
| 2016 | ICML | Principal Component Projection Without Principal Component Analysis. | Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford |
| 2016 | ICML | Faster Eigenvector Computation via Shift-and-Invert Preconditioning. | Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford |
| 2016 | ICML | Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis. | Rong Ge, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford |
| 2016 | STOC | Geometric median in nearly linear time. | Michael B. Cohen, Yin Tat Lee, Gary L. Miller, Jakub Pachocki, Aaron Sidford |
| 2016 | STOC | Routing under balance. | Alina Ene, Gary L. Miller, Jakub Pachocki, Aaron Sidford |
| 2015 | COLT | Competing with the Empirical Risk Minimizer in a Single Pass. | Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford |
| 2015 | FOCS | Efficient Inverse Maintenance and Faster Algorithms for Linear Programming. | Yin Tat Lee, Aaron Sidford |
| 2015 | FOCS | A Faster Cutting Plane Method and its Implications for Combinatorial and Convex Optimization. | Yin Tat Lee, Aaron Sidford, Sam Chiu-wai Wong |
| 2015 | ICML | Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization. | Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford |
| 2015 | WADS | Polylogarithmic Fully Retroactive Priority Queues via Hierarchical Checkpointing. | Erik D. Demaine, Tim Kaler, Quanquan C. Liu, Aaron Sidford, Adam Yedidia |
| 2014 | FOCS | Single Pass Spectral Sparsification in Dynamic Streams. | Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford |
| 2014 | FOCS | Path Finding Methods for Linear Programming: Solving Linear Programs in (vrank) Iterations and Faster Algorithms for Maximum Flow. | Yin Tat Lee, Aaron Sidford |
| 2014 | SODA | An Almost-Linear-Time Algorithm for Approximate Max Flow in Undirected Graphs, and its Multicommodity Generalizations. | Jonathan A. Kelner, Yin Tat Lee, Lorenzo Orecchia, Aaron Sidford |
| 2013 | FOCS | Efficient Accelerated Coordinate Descent Methods and Faster Algorithms for Solving Linear Systems. | Yin Tat Lee, Aaron Sidford |
| 2013 | STOC | A simple, combinatorial algorithm for solving SDD systems in nearly-linear time. | Jonathan A. Kelner, Lorenzo Orecchia, Aaron Sidford, Zeyuan Allen Zhu |