They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission . Aaron Sidford, Gregory Valiant, Honglin Yuan COLT, 2022 arXiv | pdf. Google Scholar, The Complexity of Infinite-Horizon General-Sum Stochastic Games, The Complexity of Optimizing Single and Multi-player Games, A Near-Optimal Method for Minimizing the Maximum of N Convex Loss Functions, On the Sample Complexity for Average-reward Markov Decision Processes, Stochastic Methods for Matrix Games and its Applications, Acceleration with a Ball Optimization Oracle, Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG, The Complexity of Infinite-Horizon General-Sum Stochastic Games
! I am fortunate to be advised by Aaron Sidford .
SODA 2023: 4667-4767. If you see any typos or issues, feel free to email me.
Improved Lower Bounds for Submodular Function Minimization
Contact: dwoodruf (at) cs (dot) cmu (dot) edu or dpwoodru (at) gmail (dot) com CV (updated July, 2021) [i14] Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian: ReSQueing Parallel and Private Stochastic Convex Optimization. Improves the stochas-tic convex optimization problem in parallel and DP setting.
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Verified email at stanford.edu - Homepage. We are excited to have Professor Sidford join the Management Science & Engineering faculty starting Fall 2016.
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I often do not respond to emails about applications. Email: sidford@stanford.edu. In Symposium on Discrete Algorithms (SODA 2018) (arXiv), Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes, Efficient (n/) Spectral Sketches for the Laplacian and its Pseudoinverse, Stability of the Lanczos Method for Matrix Function Approximation.
rl1 I am broadly interested in mathematics and theoretical computer science. Selected for oral presentation. 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. International Colloquium on Automata, Languages, and Programming (ICALP), 2022, Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods
We establish lower bounds on the complexity of finding $$-stationary points of smooth, non-convex high-dimensional functions using first-order methods. which is why I created a
>CV >code >contact; My PhD dissertation, Algorithmic Approaches to Statistical Questions, 2012. 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.
Aaron Sidford We organize regular talks and if you are interested and are Stanford affiliated, feel free to reach out (from a Stanford email). "FV %H"Hr
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Research Institute for Interdisciplinary Sciences (RIIS) at
with Aaron Sidford
[pdf] [talk] [poster]
NeurIPS Smooth Games Optimization and Machine Learning Workshop, 2019, Variance Reduction for Matrix Games
Prof. Erik Demaine TAs: Timothy Kaler, Aaron Sidford [Home] [Assignments] [Open Problems] [Accessibility] sample frame from lecture videos Data structures play a central role in modern computer science. {{{;}#q8?\. Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, and Kevin Tian. [pdf]
with Kevin Tian and Aaron Sidford
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 With Rong Ge, Chi Jin, Sham M. Kakade, and Praneeth Netrapalli. The authors of most papers are ordered alphabetically. 113 * 2016: The system can't perform the operation now. Before attending Stanford, I graduated from MIT in May 2018. ICML Workshop on Reinforcement Learning Theory, 2021, Variance Reduction for Matrix Games
Towards this goal, some fundamental questions need to be solved, such as how can machines learn models of their environments that are useful for performing tasks . Email: [name]@stanford.edu My research interests lie broadly in optimization, the theory of computation, and the design and analysis of algorithms. by Aaron Sidford. Secured intranet portal for faculty, staff and students. Applying this technique, we prove that any deterministic SFM algorithm . Conference Publications 2023 The Complexity of Infinite-Horizon General-Sum Stochastic Games With Yujia Jin, Vidya Muthukumar, Aaron Sidford To appear in Innovations in Theoretical Computer Science (ITCS 2023) (arXiv) 2022 Optimal and Adaptive Monteiro-Svaiter Acceleration With Yair Carmon, International Conference on Machine Learning (ICML), 2020, Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG
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(ACM Doctoral Dissertation Award, Honorable Mention.) 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. Enrichment of Network Diagrams for Potential Surfaces. Simple MAP inference via low-rank relaxations. Here are some lecture notes that I have written over the years. Eigenvalues of the laplacian and their relationship to the connectedness of a graph.
[PDF] Faster Algorithms for Computing the Stationary Distribution Aaron Sidford is an assistant professor in the departments of Management Science and Engineering and Computer Science at Stanford University. missouri noodling association president cnn.
Aaron Sidford | Stanford Online Aaron Sidford - Teaching I am fortunate to be advised by Aaron Sidford.
aaron sidford cv Navajo Math Circles Instructor.
Yang P. Liu - GitHub Pages Nearly Optimal Communication and Query Complexity of Bipartite Matching . ", "A new Catalyst framework with relaxed error condition for faster finite-sum and minimax solvers. /CreationDate (D:20230304061109-08'00')
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. I am a fifth year Ph.D. student in Computer Science at Stanford University co-advised by Gregory Valiant and John Duchi.
Publications | Jakub Pachocki - Harvard University Google Scholar; Probability on trees and . David P. Woodruff . In each setting we provide faster exact and approximate algorithms. Management Science & Engineering [pdf] [poster]
Michael B. Cohen, Yin Tat Lee, Gary L. Miller, Jakub Pachocki, and Aaron Sidford. 2022 - current Assistant Professor, Georgia Institute of Technology (Georgia Tech) 2022 Visiting researcher, Max Planck Institute for Informatics. Faculty and Staff Intranet. Here is a slightly more formal third-person biography, and here is a recent-ish CV. We will start with a primer week to learn the very basics of continuous optimization (July 26 - July 30), followed by two weeks of talks by the speakers on more advanced .
Publications | Salil Vadhan By using this site, you agree to its use of cookies. Stanford, CA 94305 Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford. [pdf] [poster]
CV; Theory Group; Data Science; CSE 535: Theory of Optimization and Continuous Algorithms. ", "Collection of new upper and lower sample complexity bounds for solving average-reward MDPs.
This work characterizes the benefits of averaging techniques widely used in conjunction with stochastic gradient descent (SGD). [c7] Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian: Private Convex Optimization in General Norms. how . [pdf] [slides]
Nima Anari, Yang P. Liu, Thuy-Duong Vuong, Maximum Flow and Minimum-Cost Flow in Almost Linear Time, FOCS 2022, Best Paper Before attending Stanford, I graduated from MIT in May 2018. Optimal Sublinear Sampling of Spanning Trees and Determinantal Point Processes via Average-Case Entropic Independence, FOCS 2022
Lower Bounds for Finding Stationary Points II: First-Order Methods Title. ", "About how and why coordinate (variance-reduced) methods are a good idea for exploiting (numerical) sparsity of data. Lower bounds for finding stationary points II: first-order methods. Aleksander Mdry; Generalized preconditioning and network flow problems
Aviv Tamar - Reinforcement Learning Research Labs - Technion However, many advances have come from a continuous viewpoint. Links. Aaron Sidford is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). Group Resources. with Yair Carmon, Arun Jambulapati and Aaron Sidford
Alcatel One Touch Flip Phone - New Product Recommendations, Promotions In particular, this work presents a sharp analysis of: (1) mini-batching, a method of averaging many . I am an assistant professor in the department of Management Science and Engineering and the department of Computer Science at Stanford University. riba architectural drawing numbering system; fort wayne police department gun permit; how long does chambord last unopened; wayne county news wv obituaries Department of Electrical Engineering, Stanford University, 94305, Stanford, CA, USA Conference of Learning Theory (COLT), 2022, RECAPP: Crafting a More Efficient Catalyst for Convex Optimization
CoRR abs/2101.05719 ( 2021 ) I am currently a third-year graduate student in EECS at MIT working under the wonderful supervision of Ankur Moitra. F+s9H Another research focus are optimization algorithms. Winter 2020 Teaching assistant for EE364a: Convex Optimization I taught by John Duchi, Fall 2018 Teaching assitant for CS265/CME309: Randomized Algorithms and Probabilistic Analysis, Fall 2019 taught by Greg Valiant. 2021 - 2022 Postdoc, Simons Institute & UC .
Aaron Sidford receives best paper award at COLT 2022 Done under the mentorship of M. Malliaris. Some I am still actively improving and all of them I am happy to continue polishing. 2013. Their, This "Cited by" count includes citations to the following articles in Scholar. /Filter /FlateDecode The design of algorithms is traditionally a discrete endeavor. stream
David P. Woodruff - Carnegie Mellon University ICML, 2016. publications by categories in reversed chronological order. . I received a B.S. Assistant Professor of Management Science and Engineering and of Computer Science.
This site uses cookies from Google to deliver its services and to analyze traffic. Anup B. Rao. Stability of the Lanczos Method for Matrix Function Approximation Cameron Musco, Christopher Musco, Aaron Sidford ACM-SIAM Symposium on Discrete Algorithms (SODA) 2018. This is the academic homepage of Yang Liu (I publish under Yang P. Liu). 2023. .
/Creator (Apache FOP Version 1.0) ", "A short version of the conference publication under the same title. Computer Science. . A nearly matching upper and lower bound for constant error here! the Operations Research group.
. We provide a generic technique for constructing families of submodular functions to obtain lower bounds for submodular function minimization (SFM).