Information about your use of this site is shared with Google. Stanford University Conference on Learning Theory (COLT), 2015. with Vidya Muthukumar and Aaron Sidford D Garber, E Hazan, C Jin, SM Kakade, C Musco, P Netrapalli, A Sidford. Aaron's research interests lie in optimization, the theory of computation, and the . Associate Professor of . Research Interests: My research interests lie broadly in optimization, the theory of computation, and the design and analysis of algorithms. This site uses cookies from Google to deliver its services and to analyze traffic. Authors: Michael B. Cohen, Jonathan Kelner, Rasmus Kyng, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford Download PDF Abstract: We show how to solve directed Laplacian systems in nearly-linear time. Aaron Sidford, Gregory Valiant, Honglin Yuan COLT, 2022 arXiv | pdf. with Yair Carmon, Aaron Sidford and Kevin Tian Sampling random spanning trees faster than matrix multiplication Faculty Spotlight: Aaron Sidford. aaron sidford cvnatural fibrin removalnatural fibrin removal In this talk, I will present a new algorithm for solving linear programs. Previously, I was a visiting researcher at the Max Planck Institute for Informatics and a Simons-Berkeley Postdoctoral Researcher. Page 1 of 5 Aaron Sidford Assistant Professor of Management Science and Engineering and of Computer Science CONTACT INFORMATION Administrative Contact Jackie Nguyen - Administrative Associate [5] Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian. [pdf] [poster] My broad research interest is in theoretical computer science and my focus is on fundamental mathematical problems in data science at the intersection of computer science, statistics, optimization, biology and economics. In particular, it achieves nearly linear time for DP-SCO in low-dimension settings. Conference of Learning Theory (COLT), 2022, RECAPP: Crafting a More Efficient Catalyst for Convex Optimization Aaron Sidford - Teaching (, In Symposium on Foundations of Computer Science (FOCS 2015) (, In Conference on Learning Theory (COLT 2015) (, In International Conference on Machine Learning (ICML 2015) (, In Innovations in Theoretical Computer Science (ITCS 2015) (, In Symposium on Fondations of Computer Science (FOCS 2013) (, In Symposium on the Theory of Computing (STOC 2013) (, Book chapter in Building Bridges II: Mathematics of Laszlo Lovasz, 2020 (, Journal of Machine Learning Research, 2017 (. [name] = yangpliu, Optimal Sublinear Sampling of Spanning Trees and Determinantal Point Processes via Average-Case Entropic Independence, Maximum Flow and Minimum-Cost Flow in Almost Linear Time, Online Edge Coloring via Tree Recurrences and Correlation Decay, Fully Dynamic Electrical Flows: Sparse Maxflow Faster Than Goldberg-Rao, Discrepancy Minimization via a Self-Balancing Walk, Faster Divergence Maximization for Faster Maximum Flow. %PDF-1.4 with Arun Jambulapati, Aaron Sidford and Kevin Tian With Yosheb Getachew, Yujia Jin, Aaron Sidford, and Kevin Tian (2023). Student Intranet. I was fortunate to work with Prof. Zhongzhi Zhang. Mail Code. Aaron Sidford is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). He received his PhD from the Electrical Engineering and Computer Science Department at the Massachusetts Institute of Technology, where he was advised by Jonathan Kelner. Aaron Sidford | Management Science and Engineering theses are protected by copyright. I maintain a mailing list for my graduate students and the broader Stanford community that it is interested in the work of my research group. I am an assistant professor in the department of Management Science and Engineering and the department of Computer Science at Stanford University. << Neural Information Processing Systems (NeurIPS, Oral), 2020, Coordinate Methods for Matrix Games Management Science & Engineering Thesis, 2016. pdf. Aaron Sidford joins Stanford's Management Science & Engineering department, launching new winter class CS 269G / MS&E 313: "Almost Linear Time Graph Algorithms." ", "A low-bias low-cost estimator of subproblem solution suffices for acceleration! Mary Wootters - Google Enrichment of Network Diagrams for Potential Surfaces. dblp: Daogao Liu aaron sidford cv Some I am still actively improving and all of them I am happy to continue polishing. The following articles are merged in Scholar. Aaron Sidford - Stanford University She was 19 years old and looking - freewareppc.com Microsoft Research Faculty Fellowship 2020: Researchers in academia at . Lower bounds for finding stationary points I, Accelerated Methods for NonConvex Optimization, SIAM Journal on Optimization, 2018 (arXiv), Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification. Janardhan Kulkarni, Yang P. Liu, Ashwin Sah, Mehtaab Sawhney, Jakub Tarnawski, Fully Dynamic Electrical Flows: Sparse Maxflow Faster Than Goldberg-Rao, FOCS 2021 I am fortunate to be advised by Aaron Sidford . Personal Website. resume/cv; publications. Yair Carmon. Many of these algorithms are iterative and solve a sequence of smaller subproblems, whose solution can be maintained via the aforementioned dynamic algorithms. In each setting we provide faster exact and approximate algorithms. small tool to obtain upper bounds of such algebraic algorithms. aaron sidford cvis sea bass a bony fish to eat. My research interests lie broadly in optimization, the theory of computation, and the design and analysis of algorithms. Neural Information Processing Systems (NeurIPS), 2021, Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss Instructor: Aaron Sidford Winter 2018 Time: Tuesdays and Thursdays, 10:30 AM - 11:50 AM Room: Education Building, Room 128 Here is the course syllabus. ", "Faster algorithms for separable minimax, finite-sum and separable finite-sum minimax. Research interests : Data streams, machine learning, numerical linear algebra, sketching, and sparse recovery.. data structures) that maintain properties of dynamically changing graphs and matrices -- such as distances in a graph, or the solution of a linear system. to appear in Neural Information Processing Systems (NeurIPS), 2022, Regularized Box-Simplex Games and Dynamic Decremental Bipartite Matching [pdf] [slides] to appear in Innovations in Theoretical Computer Science (ITCS), 2022, Optimal and Adaptive Monteiro-Svaiter Acceleration [PDF] Faster Algorithms for Computing the Stationary Distribution If you see any typos or issues, feel free to email me. /Creator (Apache FOP Version 1.0) with Yair Carmon, Arun Jambulapati and Aaron Sidford Allen Liu. ", "About how and why coordinate (variance-reduced) methods are a good idea for exploiting (numerical) sparsity of data. Before Stanford, I worked with John Lafferty at the University of Chicago. CV (last updated 01-2022): PDF Contact. Aaron Sidford - Selected Publications 22nd Max Planck Advanced Course on the Foundations of Computer Science theory and graph applications. 2019 (and hopefully 2022 onwards Covid permitting) For more information please watch this and please consider donating here! ", "Collection of variance-reduced / coordinate methods for solving matrix games, with simplex or Euclidean ball domains. IEEE, 147-156. with Hilal Asi, Yair Carmon, Arun Jambulapati and Aaron Sidford I am a fourth year PhD student at Stanford co-advised by Moses Charikar and Aaron Sidford. endobj . Our method improves upon the convergence rate of previous state-of-the-art linear programming . In Sidford's dissertation, Iterative Methods, Combinatorial . International Colloquium on Automata, Languages, and Programming (ICALP), 2022, Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods (arXiv pre-print) arXiv | pdf, Annie Marsden, R. Stephen Berry. Roy Frostig, Sida Wang, Percy Liang, Chris Manning. Np%p `a!2D4! Aaron Sidford Stanford University Verified email at stanford.edu. The design of algorithms is traditionally a discrete endeavor. 2023. . This improves upon previous best known running times of O (nr1.5T-ind) due to Cunningham in 1986 and (n2T-ind+n3) due to Lee, Sidford, and Wong in 2015. NeurIPS Smooth Games Optimization and Machine Learning Workshop, 2019, Variance Reduction for Matrix Games 2013. with Yair Carmon, Kevin Tian and Aaron Sidford Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford. I received my PhD from the department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology where I was advised by Professor Jonathan Kelner. pdf, Sequential Matrix Completion. We provide a generic technique for constructing families of submodular functions to obtain lower bounds for submodular function minimization (SFM). Parallelizing Stochastic Gradient Descent for Least Squares Regression ", "An attempt to make Monteiro-Svaiter acceleration practical: no binary search and no need to know smoothness parameter! I graduated with a PhD from Princeton University in 2018. Michael B. Cohen, Yin Tat Lee, Gary L. Miller, Jakub Pachocki, and Aaron Sidford. SODA 2023: 4667-4767. [pdf] Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, and Kevin Tian. Aaron Sidford's research works | Stanford University, CA (SU) and other Nima Anari, Yang P. Liu, Thuy-Duong Vuong, Maximum Flow and Minimum-Cost Flow in Almost Linear Time, FOCS 2022, Best Paper Overview This class will introduce the theoretical foundations of discrete mathematics and algorithms. My long term goal is to bring robots into human-centered domains such as homes and hospitals.
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